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Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful and innovative technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. We are passionate about user-centred design, agile delivery, and building digital services that make a real difference — and we're now scaling that expertise into large, high-stakes AI adoption programmes across the public sector. We're looking for a Lead AI Engineer to be the hands-on technical builder at the core of a large-scale AI Operating Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems — semantic search, RAG pipelines, and broader generative AI capability — integrated into complex legacy and multi-cloud environments handling high-volume, sensitive public sector data. You’ll work inside a collaborative "Rainbow Team" alongside civil servants and the wider delivery team, staying close to the code while also mentoring engineers and helping build the internal capability the department needs to eventually run these systems without long‑term reliance on external suppliers. Design, build, and ship production AI components — RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers — writing high-quality, tested, maintainable code and staying close to implementation rather than delegating it away. Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day. Implement the guardrails the Architect designs — bias mitigation checks, evaluation harnesses, human-in-the-loop review points — so that Responsible AI principles (ATRS alignment, NCSC "Secure by Design," meaningful human control) are enforced in the running system, not just on paper. Build AI services to be secure-by-default and observable in production: logging, monitoring, alerting, and rollback paths appropriate for sensitive public‑sector data and high‑availability requirements. Work within the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs-as-Code" practices to pair with and upskill internal government engineers, so capability genuinely transfers rather than staying locked in the consultancy team. Favour low‑modality, resource‑efficient designs where they meet the need — right‑sizing models and infrastructure rather than defaulting to the largest/most expensive option — in line with the programme's Green AI and Net‑Zero commitments. Loosely mapped to the Government Digital and Data (DDaT) framework, at Lead Engineer level: • Coding and Scripting (Expert) — writing production‑grade, well‑tested code; setting standards for others; comfortable owning components end‑to‑end., • Systems Design (Practitioner) — designing components that integrate cleanly into a wider, architect‑defined system; understanding trade‑offs across the stack., • Data Engineering (Practitioner) — building reliable pipelines to ingest, clean, and prepare data (including unstructured/legacy sources) for AI consumption., • DevOps / Continuous Delivery (Practitioner) — CI/CD pipelines, infrastructure‑as‑code, and automated deployment for AI workloads specifically (not just conventional web services)., • Testing & Evaluation (Practitioner) — beyond conventional unit/integration testing, building evaluation harnesses for AI system quality: retrieval accuracy, hallucination rate, bias/fairness checks., • Problem Solving (Practitioner) — diagnosing and resolving complex, ambiguous technical issues under production pressure., • Agile Working (Practitioner) — delivering iteratively within a blended, multidisciplinary team including civil servants. Given the scale of this programme, direct hands‑on depth across the AI engineering stack is essential: • Strong general‑purpose programming (most commonly Python) applied to AI/ML systems, • Semantic search, vector/embedding infrastructure, and RAG pipeline construction, • LLM orchestration and agentic frameworks (e.g. LangChain/LlamaIndex-style tooling, multi‑agent patterns), • Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing), • LLMOps/MLOps — model versioning, deployment, monitoring, and rollback for AI services in production, • Cloud‑native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling, • Containerisation and infrastructure‑as‑code for repeatable, auditable deployments, • Secure‑by‑design engineering appropriate to sensitive public‑sector data, • AWS / Azure / GCP certifications (associate or professional level), • Prior delivery of AI or digital services within UK central government or wider public sector, • Experience fine‑tuning or adapting open‑source/foundation models for a specific domain, • Open‑source contributions or active engagement in AI/ML engineering communities, • Experience designing for sustainability/Green IT commitments, • The technological capabilities can span a wide range of AI and automation tools, including Virtual Assistants, Robotic Process Automation (RPA), Computer Vision, Natural Language Processing (NLP), Machine Learning, Deep Learning, Generative AI, Frontier LLMs, and Predictive AI. A strong candidate would have experience/exposure to nuances of these tools/technologies. Hybrid, based from Newcastle upon Tyne, with on‑site attendance required for workshops, knowledge‑transfer sessions, and onboarding. All production system and data access must be performed solely from within the UK. • Collaboration — we are stronger as a team than as individuals; we tackle problems and celebrate wins together., • Create Value Early — we find the quickest route from idea to product, because our clients rely on us to do what's best., • Integrity — teamwork requires trust; we can always be relied upon to uphold the highest standards., • Commitment — no matter what, no matter how, we give our 100% to keeping our promises and achieving our goals., • Diversity and Inclusion — we believe diversity drives innovation and better outcomes, and we're committed to an inclusive environment where every individual is valued, respected, and supported. We welcome applications from candidates of all backgrounds, including women, people with disabilities, and diverse communities, as well as those seeking flexible working arrangements. As a Disability Confident Level 1 employer, we provide reasonable adjustments throughout recruitment and employment to ensure equal opportunity for all. #J-18808-Ljbffr

Newcastle, United Kingdom | Posted on 11/09/2026 Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful and innovative technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. We are passionate about user-centred design, agile delivery, and building digital services that make a real difference - and we're now scaling that expertise into large, high-stakes AI adoption programmes across the public sector. We're looking for a Lead AI Engineer to be the hands-on technical builder at the core of a large-scale AI Operating Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside a collaborative "Rainbow Team" alongside civil servants and the wider delivery team, staying close to the code while also mentoring engineers and helping build the internal capability the department needs to eventually run these systems without long-term reliance on external suppliers. • Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating it away., • Technical Leadership Within the Squad Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day., • Responsible AI in Practice Implement the guardrails the Architect designs - bias mitigation checks, evaluation harnesses, human-in-the-loop review points - so that Responsible AI principles (ATRS alignment, NCSC "Secure by Design, " meaningful human control) are enforced in the running system, not just on paper., • Reliability, Security & Observability Build AI services to be secure-by-default and observable in production: logging, monitoring, alerting, and rollback paths appropriate for sensitive public-sector data and high-availability requirements., • Knowledge Transfer & Capability Uplift Work within the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs-as-Code" practices to pair with and upskill internal government engineers, so capability genuinely transfers rather than staying locked in the consultancy team., • Efficient, Sustainable Engineering Favour low-modality, resource-efficient designs where they meet the need - right-sizing models and infrastructure rather than defaulting to the largest/most expensive option - in line with the programme's Green AI and Net Zero commitments. Loosely mapped to the Government Digital and Data (DDaT) framework, at Lead Engineer level: • Coding and Scripting (Expert) - writing production-grade, well-tested code; setting standards for others; comfortable owning components end-to-end., • Systems Design (Practitioner) - designing components that integrate cleanly into a wider, architect-defined system; understanding trade-offs across the stack., • Data Engineering (Practitioner) - building reliable pipelines to ingest, clean, and prepare data (including unstructured/Legacy sources) for AI consumption., • DevOps/Continuous Delivery (Practitioner) - CI/CD pipelines, infrastructure-as-code, and automated deployment for AI workloads specifically (not just conventional web services)., • Testing & Evaluation (Practitioner) - beyond conventional unit/integration testing, building evaluation harnesses for AI system quality: retrieval accuracy, hallucination rate, bias/fairness checks., • Problem Solving (Practitioner) - diagnosing and resolving complex, ambiguous technical issues under production pressure., • Agile Working (Practitioner) - delivering iteratively within a blended, multidisciplinary team including civil servants. Given the scale of this programme, direct hands-on depth across the AI engineering stack is essential: • Strong general-purpose programming (most commonly Python) applied to AI/ML systems, • Semantic search, vector/embedding infrastructure, and RAG pipeline construction, • LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns), • Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing), • LLMOps/MLOps - model versioning, deployment, monitoring, and rollback for AI services in production, • Cloud-native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling, • Containerisation and infrastructure-as-code for repeatable, auditable deployments, • Secure-by-design engineering appropriate to sensitive public-sector data, • AWS/Azure/GCP certifications (associate or professional level), • Prior delivery of AI or digital services within UK central government or wider public sector, • Experience fine-tuning or adapting open-source/foundation models for a specific domain, • Open-source contributions or active engagement in AI/ML engineering communities, • Experience designing for sustainability/Green IT commitments, • The technological capabilities can span a wide range of AI and automation tools, including Virtual Assistants, Robotic Process Automation (RPA), Computer Vision, Natural Language Processing (NLP), Machine Learning, Deep Learning, Generative AI, Frontier LLMs, and Predictive AI. A strong candidate would have experience/exposure to nuances of these tools/technologies. Hybrid, based from Newcastle upon Tyne, with on-site attendance required for workshops, knowledge-transfer sessions, and onboarding. All production system and data access must be performed solely from within the UK. Our values: • Collaboration- we are stronger as a team than as individuals; we tackle problems and celebrate wins together., • Create Value Early- we find the quickest route from idea to product, because our clients rely on us to do what's best., • Integrity- teamwork requires trust; we can always be relied upon to uphold the highest standards., • Commitment- no matter what, no matter how, we give our 100% to keeping our promises and achieving our goals., • Diversity and Inclusion- we believe diversity drives innovation and better outcomes, and we're committed to an inclusive environment where every individual is valued, respected, and supported. We welcome applications from candidates of all backgrounds, including women, people with disabilities, and diverse communities, as well as those seeking flexible working arrangements. As a Disability Confident Level 1 employer, we provide reasonable adjustments throughout recruitment and employment to ensure equal opportunity for all. #J-18808-Ljbffr

Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK. You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi‑agent solution in production, you have owned the evaluation harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production‑grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle. This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. • Design and build production‑grade agentic solutions end‑to‑end: multi‑agent orchestration, RAG pipelines, policy‑based routing, tool invocation, memory management, and lifecycle observability, • Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets, • Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open‑source models — with fallback routing, token, cost, and latency management, • Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring, • Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases, design, prototype, and deploy agentic solutions — workshops, proofs of concept, code‑with sessions, and architecture walkthroughs, • Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster, • Define and use metrics to measure agent accuracy, latency, safety, and cost‑effectiveness; present findings and recommendations to client stakeholders in business terms, • Significant software engineering experience in production environments, • Hands‑on experience designing and deploying agentic AI solutions in a production environment — non‑negotiable, • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level, • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs, • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering, • LLMOps fundamentals: eval harness design, prompt versioning, and production observability, • Cloud‑native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm), • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience, • #LI‑EU Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent‑and innovation‑led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com Explore your next step at Accenture We believe that no one should be discriminated against because of their differences.All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law.Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. #J-18808-Ljbffr

Senior Consultant - Agentic AI / Generative AILondon, Manchester, Newcastle Bank House, GlasgowApply for this job Permanent Experienced Professionals Strategy & Transformation ID 561575-en\_GB## CAPGEMINI INVENTAt Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.We’re looking for GenAI/Agentic Engineers who want to shape the future of Machine Learning, Generative AI and Agentic AI. You will be tasked with building and deploying intelligent systems that combine cutting-edge models, agentic frameworks, and full-stack engineering to solve real business problems. If you’re excited by rapid prototyping, scaling AI products into production, and using technology to make a tangible impact, this is your place to do it.## YOUR ROLEIn this position you will play a key part in: Designing, developing, testing, and deploying both front-end and back-end components of applications within the data science and AI consulting team with a focus on GenAI and agentic solutions. · Collaborating cloud architects, data scientists, product managers, and business consultants to bring ideas to production. Design agentic workflows with HITL gates, auditability, policy controls, and robust evaluation/monitoring suitable for regulated clients Translating business challenges into AI-powered solutions, leveraging Generative and Agentic AI, data science, and analytics to deliver innovation and results to meet client standards. · Working effectively in a team, supporting your peers in delivering at pace and meeting our own high internal standards of output and delivery.As part of your role, you will also have the opportunity to contribute to the business and your own personal growth, through activities that form part of the following categories: Business Development – Using your full stack skillset to build AI Demonstrators to showcase to potential clients, contributing to proposals, RFPs, bids, client pitch contribution, and client hosting at events. Internal contribution – Campaign development, internal think-tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development. Learning & development – Training to support your career development and the skills demand within the company, certifications etc.## YOUR PROFILEWe’d love to meet someone with: Experience working in a major Consulting firm, and/or in industry but having a Consulting mindset with a proven ability to be successful in a matrixed organisation, and to enlist support and commitment from peers in selling and delivering solutions. Experience of working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out solutions. Experience of designing and developing full-stack applications across the application lifecycle, from building early PoCs, through to developing MVPs and testing them, to finally deploying a secure and scalable production-grade solution. A proven track record of successfully delivering solutions using traditional Machine Learning models, Generative AI models and using Agentic AI frameworks in a client-facing environment, by building GenAI And Agentic solutions, including data engineering in cloud environments. The ability to demonstrate the potential that AI has to offer to unlock business value.Your Technical Expertise:This list shows the technologies we work with most often. We don’t expect you to have experience in all of them - what matters is a strong foundation and a good cross-section of these skills, along with the adaptability and curiosity to learn new tools as projects demand. Languages & Frameworks: Python (3.10+), TypeScript, JavaScript (ES6+), SQL, Bash · Frontend: React.js, Next.js (App Router & Server Components), Tailwind CSS, ShadCN UI, Redux, Zustand, Jest, Cypress. Build AI product UX patterns (streaming, review loops, provenance/citations, long-running tasks, error-recovery Backend: Django (5.x+), DRF, FastAPI, Pydantic, Celery, Django Channels, Flask, RESTful APIs. Databases & Storage: PostgreSQL, MS SQL Server, MongoDB, Firestore, BigQuery, Azure Blob Storage. Cloud & DevOps: Azure (App Services, OpenAI, AKS), GCP (Vertex AI, Cloud Run), Docker, GitHub Actions, Azure DevOps, RBAC and Cost Controls. Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens. Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK.## WHAT YOU'LL LOVE ABOUT WORKING HEREWe’re a fantastic team of bright, ambitious people who love to bring the latest tech to real clients and bring it into production to make a meaningful difference. We work across both the public and private sectors, and our impact is tangible: we innovate, we deploy, and you’ll see your work come to life in the real world.Technology moves fast, and so do we. We’re a group of true tech enthusiasts who push boundaries, experiment freely, and are trusted at Capgemini to explore what’s next. Our in-house projects showcase what’s possible with the newest models and agentic frameworks, and we regularly present our work at major events and conferences.We’re looking for more people with the curiosity, drive, and self-starting spirit of real innovators. people who love technology and want to build the future with us.## NEED TO KNOWAt Capgemini we don’t just believe in inclusion, we actively go out to making it a working reality. Driven by our core values and Inclusive Futures for All campaign, we build environments where you can bring you whole self to work.We aim to build an environment where employees can enjoy a positive work-life balance. We embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas. We have also invested in wellbeing apps such as Thrive and Peppy.We are a Disability Confident Employer Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who: Declare they have a disability, and Meet the minimum essential criteria for the role.Please opt in during the application process.## ABOUT CAPGEMINICapgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.Make it real. | www.capgemini.com #J-18808-Ljbffr

Working Pattern: Remote-first, with 1–2 days per month in the office Salary: Up to £80,000 Contract: Full-time We’re looking for an AI Engineer to help build and scale intelligent, agent-driven systems that operate reliably in real-world production environments. This role sits at the intersection of software engineering, cloud architecture, and modern AI platforms. You’ll be trusted to design systems that don’t just work today, but continue to evolve as models, tooling, and requirements inevitably change. • Building and maintaining robust backend services using Node.js and TypeScript, • Designing and operating agent-based AI systems, from orchestration through to deployment, • Managing conversational context, memory, and state across complex workflows, • Integrating internal services and third-party tools through clean, well-structured APIs, • Implementing observability, evaluation, and cost controls for AI workloads, • Designing cloud-native systems on AWS, with a focus on scalability and resilience, • Contributing to architectural decisions across distributed, event-driven systems, • Working closely with product and engineering teams to turn ideas into production-ready solutions, • Significant experience building production-grade systems with TypeScript and Node.js, • Hands-on experience with agentic AI frameworks or similar orchestration platforms, • A strong understanding of:, • Multi-agent workflow orchestration, • Context and memory management in AI-driven applications, • Tooling, MCPs, and API-based integrations, • Monitoring, evaluation, and cost awareness for AI systems, • Deep experience working with Amazon Web Services (AWS) and cloud-native patterns, • Solid knowledge of modern system architectures, including microservices and event-driven designs, • A proven ability to design systems that remain flexible as models, tools, and business needs evolve, • Salary up to £80,000, • Remote-first role with minimal office time, • Opportunity to work on cutting-edge agent-based AI systems, • High ownership and real influence over technical direction, • A pragmatic, engineering-led culture focused on long-term quality #J-18808-Ljbffr

Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. • UK & Ireland's premier AWS, Microsoft & Oracle partner, • 3300+ strong, €350/£300m revenue business, • 10+ years as a Great Place to Work in Ireland & UK, • Best Workplace for Women in the UK & Ireland by GPTW, • Best Workplace for Wellbeing in the UK by GPTW We’re a core valuesdriven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you. We are seeking a hands‑on AI/ML Engineer to build, deploy, and optimize machine learning and Generative AI solutions. The role focuses on developing production‑grade AI applications, integrating AI models into business systems, and supporting the full AI development lifecycle. The ideal candidate is passionate about modern AI technologies, software engineering best practices, and delivering reliable AI solutions at scale. AI Application Development • Design, build, and maintain AI-powered applications and services., • Develop and deploy Machine Learning and Generative AI solutions., • Build Retrieval-Augmented Generation (RAG) systems and AI agents., • Integrate foundation models and APIs into enterprise applications., • Create reusable AI components and frameworks. Machine Learning Engineering • Train, fine‑tune, evaluate, and deploy ML models., • Develop feature engineering and model evaluation pipelines., • Implement model monitoring and performance tracking., • Optimize model inference performance and cost efficiency. Generative AI Engineering • Develop LLM‑based applications and workflows., • Build prompt templates, agent frameworks, and orchestration pipelines., • Implement vector search and knowledge retrieval systems., • Design evaluation frameworks for AI quality, safety, and reliability., • Improve hallucination mitigation and response accuracy. MLOps & Deployment • Design and automate ML model training, validation, and retraining pipelines., • Version and manage datasets, features, and model artefacts using tools such as MLflow or similar., • Deploy and serve ML models via REST APIs or batch inference at scale on Databricks, Snowflake or similar., • Monitor model performance in production, detecting drift and degradation., • Manage feature stores and ensure data pipeline reliability for ML workloads., • Implement experiment tracking and reproducibility across the model lifecycle. Collaboration • Work closely with Solution Architects, Product Managers, and Engineering Teams., • Participate in code reviews and technical design discussions., • Support testing, deployment, and ongoing optimisation activities. Programming & Engineering • Strong proficiency in:, • Python, • SQL, • Experience with:, • Scikit-learn, • PyTorch and/or TensorFlow, • Hugging Face, • Main AI services from leading cloud service and model providers, • Supervised and unsupervised learning, • Model evaluation, • Feature engineering, • Statistical concepts Generative AI • Practical experience building:, • RAG systems, • AI agents, • LLM‑powered applications, • Vector search solutions, • Familiarity with:, • LangChain, • LlamaIndex, • Semantic Kernel, • LangGraph Cloud & Infrastructure • Experience with AWS., • Docker and containerization., • Kubernetes (preferred)., • CI/CD pipelines and DevOps practices. Professional Experience • 3+ years in ML engineering or data science, with demonstrable experience deploying models to production and building Gen AI applications including RAG systems, LLM integration, or agentic workflows, • Demonstrated experience delivering AI solutions into production environments. Why Version 1? • Share in our success with our Quarterly Performance‑Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits, • Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme, • Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance, • Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme, • Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies, • Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat, • Reward schemes including Version 1’s Annual Excellence Awards & ‘Call‑Out’ platform., • Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. Version 1 is an equal opportunities employer. We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring. We want every candidate to have a positive and accessible recruitment experience. If you need reasonable adjustments at any stage of the process, please contact at Version 1. We will consider all requests carefully, respectfully and confidentially. watch?v=F_d3ELTH5zo #J-18808-Ljbffr

Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Your locationYour locationIndustriesChoose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Bristol, London, Newcastle, Manchester, Birmingham# Lead AI Engineer## About the RoleLead AI Engineer We’re seeking a Lead AI Engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus of this role is to bridge the gap between AI prototypes and embedding data and AI solutions in business. You’ll scale AI solutions responsibly and reliably, ensuring they move from lab to live by building the right solutions, practices, and guardrails while ensuring business value creation and impact. In this position you will play a key part in: Designing and delivering end-to-end AI/ML systems, from data preparation and model development to model deployment, feature stores, model management and monitoring model management Delivering solutions using the latest GenAI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex and other Translating AI use case requirements into data and AI architectures using the most suitable cloud services across hyperscalars Leading multi-disciplinary teams to execute complex requirements Architecting and implementing Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS. Embedding safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible. Collaborating with Product Managers, Data Scientists and Business stakeholders to ensure AI solutions drives business value and impact.As part of your role, you will also have the opportunity to contribute to the business and your own personal growth, through activities that form part of the following categories: Business Development - Build client-ready demos/POVs, support proposals and technical deep-dives, and showcase delivery patterns. Internal contribution - Build reusable assets and frameworks that accelerate delivery across accounts and support capability development by contributing to our internal communities and best practices. Capability Development - Contribute to thought leadership, blog posts, or internal accelerator development in emerging AI engineering topics such as Agentic AI, LLMOps, or evaluation frameworks. Experience working in a major Consulting firm, and/or in industry but having a Consulting mindset with a proven ability to be successful in a matrixed organisation, and to enlist support and commitment from peers in selling and delivering solutions. Experience of working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out solutions. Experience of designing and implementing MLOPs strategy and framework and proven track record in designing and delivering AI/ML solutions at scale, from concept to production. Deep understanding of Generative AI and Agentic AI — RAG pipelines, embeddings, evaluation harnesses, and orchestration frameworks. Experience designing cloud-native data and AI architectures across Azure, GCP, AWS and/or Databricks.* The ability to demonstrate the potential that scaling AI unlocks business value and impact.## Experience RequiredYour Technical Expertise:This list shows the technologies we work with most often. We don’t expect you to have experience in all of them - what matters is a strong foundation and a good cross-section of these skills, along with the adaptability and curiosity to learn new tools as projects demand. We like to innovate and need self-driven, fast-paced learners in our team. Experience with deploying and scaling AI solutions using at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker) Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK Hands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar. Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar).* Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes. Nice to haves: Familiarity with evaluating AI system performance, including prompt evaluation, A/B testing, and quality assessment frameworks. Understanding of modern data patterns: lakehouse architectures, vector databases, and relational/NoSQL stores* Familiarity with API gateways, event streaming and general integration patterns. Eligibility:* You need to have resided in the UK for the last 5 years to be able to apply for this roleWHAT YOU'LL LOVE ABOUT WORKING HEREWe’re a fantastic team of bright, ambitious people who love bringing the latest tech to real clients in production to make a meaningful difference. We work across both the public and private sectors, and our impact is tangible because we innovate, we deploy, and you will see your work come to life in the real world. Technology moves fast, and so do we. We’re a group of true tech enthusiasts who push boundaries, experiment freely, and are trusted at Capgemini to explore what comes next. Our in-house projects highlight what’s possible with the newest models and agentic frameworks. We’re looking for more people with the curiosity, drive, and self-starting spirit of real innovators, people who love technology and want to build the future with us.NEED TO KNOWWe are delighted to have received the “Glassdoor Best Places to work UK’ accolade for 2 consecutive years, to see what it’s like to work at Capgemini, visit our Glassdoor page At Capgemini we don’t just believe in Diversity & Inclusion, we actively go out to making it a working reality. Driven by our core values and Active Inclusion Campaign, we build environments where you can bring you whole self to work.We aim to build an environment where employees can enjoy a positive work-life balance. We embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas. We have also invested in wellbeing apps such as Thrive and Peppy. We’re also focused on using tech to have a positive social impact. So, we’re working to reduce our own carbon footprint and improve everyone’s access to a digital world. It’s something we’re really serious about. In fact, we were even named as one of the world’s most ethical companies by the Ethisphere Institute for the 10th year. When you join Capgemini, you’ll join a team that does the right thing. Whilst you will have a office base location, you must be fully flexible in terms of assignment location, as these roles may involve periods of time away from home at short notice. We offer a remuneration package which includes flexible benefits options for you to choose to suit your own personal circumstances and a variable element dependent grade and on company and personal performance.Experience levelExperienced ProfessionalsLocationBristol, London, Newcastle, Manchester, Birmingham #J-18808-Ljbffr

We are looking for a Creative Lead to join our Operations department, working cross-functionally across all delivery pods. This is a senior position responsible for setting and upholding the standard for visual design, user experience and creative delivery across our Shopify practice. You will combine exceptional hands‑on design craft with team leadership, commercial awareness and a deep understanding of how successful Shopify experiences are designed, built and maintained. You will lead the design discipline across all delivery pods, working alongside Project Managers, Development Leads, Frontend Developers, Solutions Consultants and Product Owners. Your remit will span discovery, research, creative direction, prototyping, development handoff, production design assurance and ongoing optimisation. You will create distinctive brand experiences within the capabilities of Shopify themes, including Dawn, Horizon, premium themes and our proprietary theme. You will own design architecture and partner with Development Leads on technical implementation, ensuring designs map accurately to theme capabilities and agreed component libraries. You will establish design systems that are actively used in delivery, implement effective AI‑assisted workflows, and help win standalone UX/UI and design engagements. Success means improving design quality, creativity, consistency and speed while protecting client outcomes and project profitability. This is a leadership role with hands‑on delivery responsibilities on selected strategic or complex projects. You will line manage and develop the design team, set standards across pods and support Sales and Solutions with design opportunities. Routine pod delivery will be led by assigned designers, with your oversight and support. Priorities and capacity across hands‑on delivery, management, sales support and practice development will be agreed with the Delivery Director and reviewed regularly. • Own the agency’s visual design standard, ensuring work demonstrates strong art direction, typography, composition, imagery, interaction design and brand expression., • Translate client positioning and customer needs into distinctive, commercially effective experiences, using reusable theme capabilities creatively., • Lead hands‑on design for selected enterprise or strategically important projects, setting a clear example of the expected quality., • Establish regular design critiques and quality reviews, providing specific, constructive feedback and approving key outputs before client presentation., • Balance visual ambition with accessibility, usability, performance, technical feasibility and the agreed budget., • Discovery, Research & Client Communication, • Establish standardised discovery playbooks, creative briefs, workshop templates and presentation frameworks for the design team., • Define customer journeys, user needs, business objectives, content requirements and measurable success criteria with clients and the wider project team., • Lead proportionate customer research, usability testing and analysis of behavioural data, using findings to inform and validate designs before development., • Review discovery and research outputs for completeness, technical accuracy and alignment with commercial objectives., • Train and coach designers to facilitate workshops, explain design decisions, manage feedback and present confidently to senior stakeholders., • Support complex enterprise workshops, challenging client discussions and escalations where additional creative leadership is required., • Shopify Theme‑Based Design & Merchant Usability, • Maintain a practical understanding of Dawn, Horizon, premium themes and our proprietary theme, including their sections, blocks, templates, settings and responsive behaviour., • Create and maintain Figma libraries that map accurately to the selected theme’s capabilities and implementation patterns., • Clearly identify native theme capabilities, configurable adaptations and bespoke development within proposed designs, agreeing scope and implications with Solutions and Development Leads., • Design for mobile and desktop customer journeys, with particular attention to mobile navigation, product discovery, product selection and purchase flows., • Design for merchants maintaining the website, ensuring sections and templates are practical to configure, populate and reuse., • Document content and imagery requirements, configuration options and relevant limitations so clients and delivery teams understand how designs will work in practice., • Design Systems & Integration with Development, • Build, implement and maintain scalable Figma design systems using shared tokens, variables, auto‑layout, component properties and documented patterns., • Establish agreed mappings between design components and Shopify theme sections, blocks, settings and templates, including components specific to our agency starter theme., • Work with developers to align design and code libraries through shared naming, documentation, versioning and change processes., • Specify responsive behaviour, interaction states, validation, loading, empty and error states, alongside accessibility and content guidance., • Integrate design systems into estimation, backlog refinement, development handoff, implementation and quality assurance., • Define ownership and approval processes for new components, changes and exceptions, keeping libraries accurate as production implementations evolve., • Support Theme App Extensions, checkout extensibility and headless storefront design where required by the agreed project scope, working with the relevant technical specialists. AI‑Assisted Design & Rapid Prototyping • Implement and maintain AI‑assisted workflows that improve design quality, consistency, speed or delivery cost, with clear evidence of their impact., • Evaluate and select appropriate tools for ideation, prototyping, asset production and repetitive tasks, based on delivery needs and demonstrated value., • Establish reusable briefs, prompts, reference materials and review criteria grounded in client brand guidelines, design systems and Shopify theme capabilities., • Use interactive prototypes to test customer journeys and clarify requirements, identifying where generated outputs require adaptation before theme implementation., • Maintain human review of design decisions and generated outputs, checking usability, accessibility, technical feasibility and brand accuracy., • Establish appropriate practices for client confidentiality, approved data use, asset provenance and usage rights., • Train the team, document effective workflows and measure adoption and results. Assess time savings alongside output quality, rework and tool costs., • Pod Delivery & Commercial Ownership, • Partner with PMs, Solutions Consultants and Development Leads to scope and estimate design work, identify dependencies and agree deliverables and acceptance criteria., • Contribute to capacity planning, backlog refinement and relevant delivery ceremonies, ensuring designers have realistic priorities and sufficient time for quality work., • Own design estimates and resource planning with PMs, monitoring budget adherence and addressing delivery risks early., • Manage design feedback, approval milestones and change control, making the impact of additional requirements clear., • Balance design quality with agreed timelines and budgets, supporting project profitability and reducing avoidable rework., • Maintain clear decisions, assumptions and handoff documentation so design work can move efficiently between teams., • Standalone Design Opportunities & Sales Support, • Help position and win standalone UX/UI, discovery and design engagements, including work commissioned independently of development or platform migration., • Work with Sales and Solutions to qualify opportunities, understand client needs and define a credible design approach and scope., • Lead or support proposals, pitches and portfolio presentations, communicating the commercial value of design and the agency’s differentiation., • Define deliverables and handoff arrangements for design‑only engagements, including projects implemented by a client’s internal team or another development partner., • Develop case studies that demonstrate the quality of delivered work, the team’s contribution and evidenced outcomes., • Accessibility, Production Assurance & Optimisation, • Embed accessibility requirements in research, design systems, specifications and reviews, working towards the WCAG AA standard agreed for each project., • Collaborate with developers to balance visual design with page performance and the practical constraints of production implementation., • Review implemented websites against approved designs across devices, including interactions, content, accessibility and edge cases., • Resolve design discrepancies with developers before launch and ensure agreed design acceptance criteria are met., • Use post‑launch feedback, usability findings and analytics to identify improvements and inform future work., • Agree optimisation hypotheses and evaluate outcomes with the wider team, recognising that conversion performance is influenced by factors beyond design alone., • Line Management, Mentorship & Practice Development Conduct regular one‑to‑ones, coaching, design critiques and presentation practice to develop each designer’s craft and client‑facing skills. Set clear competency expectations and progression paths covering design quality, research, Shopify knowledge, commercial awareness and delivery. Support recruitment and onboarding, assessing candidates against practical evidence and the agency’s standards. Maintain creative briefs, QA checklists, file organisation and documentation standards across pods. Monitor team capacity and capability, escalating resourcing or skills gaps and proposing practical improvements. Enterprise Shopify portfolio: A proven portfolio of live enterprise level Shopify and Shopify Plus websites demonstrating exceptional visual design, strong mobile UX and commercially effective customer journeys. Candidates must explain their personal contribution, delivery constraints and evidenced outcomes. Work must extend beyond concepts and prototypes to implemented websites. Shopify theme‑based delivery: A proven track record of designing against Shopify base theme templates, including Dawn, Horizon and premium themes. This must include component libraries that match theme sections, blocks, templates, settings and responsive behaviours, with clear distinctions between native capabilities, configuration and bespoke development. Design systems integrated with development: A proven track record of implementing high quality, scalable design systems actively used by designers and developers. Evidence must cover tokens, reusable components, documented patterns, versioning, governance, adoption and integration into planning, implementation and QA. Standalone design wins: A proven track record of winning standalone UX/UI and design projects, including engagements independent of development or migration. Candidates must explain their contribution to qualification, proposals, pitching, commercial positioning, scope and successful delivery. Successful AI implementation: A proven track record of implementing AI assistance within professional design processes, with evidence of team adoption and measurable improvements in speed, quality, consistency or cost. Candidates must explain the workflows, evaluation methods, human review and safeguards introduced. Creative leadership: Extensive eCommerce design experience within an agency or comparable delivery environment, combining hands‑on creative direction with line management, mentoring and quality ownership. Research and validation: Practical experience using customer research, usability testing and behavioural evidence to inform and validate design decisions. Enterprise stakeholder management: Experience facilitating discovery, presenting to senior stakeholders, managing competing requirements and coaching designers in client communication. Commercial delivery: Experience estimating and scoping design engagements, managing feedback and change, and delivering within agreed budgets and timelines. Cross‑functional working: Experience collaborating with PMs, Solutions Consultants and developers throughout implementation, including production design assurance and post‑launch improvement. Desirable Experience Multi‑brand and international Shopify experiences, including localisation and differing content requirements. Shopify checkout extensibility, Theme App Extensions or headless storefront projects. Experimentation and conversion optimisation programmes with measurable outcomes. Designing integrated experiences involving search, subscriptions, loyalty, personalisation or other third‑party services. Technical & Tooling Competencies Advanced Figma skills, including auto‑layout, variables, component sets, component properties, prototyping and library management. Strong knowledge of Shopify theme architecture, section and block models, theme configuration, checkout design constraints and mobile eCommerce patterns. Working understanding of HTML, CSS, JSON and Liquid, sufficient to discuss feasibility, performance implications and implementation requirements with developers. Practical knowledge of accessibility, responsive behaviour and how design decisions affect Core Web Vitals. Experience with professional asset creation and editing tools appropriate to the workflow, such as Adobe Creative Suite. Demonstrable expertise with AI‑assisted design and prototyping tools, such as Lovable, v0 or equivalent platforms; successful application matters more than familiarity with a particular vendor. Ability to interpret analytics, session recordings and usability findings using tools such as GA4, Microsoft Clarity, Hotjar or equivalents. Familiarity with iterative delivery, backlog management and documented design‑to‑development handoffs. Key Performance Indicators Specific targets will be agreed with the Delivery Director using delivery baselines and reviewed regularly. Creative and production quality: Quality review results and acceptance of implemented experiences against agreed design criteria. Client satisfaction: Feedback on creative quality, strategic guidance, communication and delivered outcomes. Delivery and budget adherence: Design milestones achieved within agreed scope, timelines and budgets, with timely change control. Design‑to‑development rework: Reduction in avoidable revisions caused by incomplete specifications, technical misalignment or inconsistent components. Design system adoption and reuse: Appropriate use of maintained components across eligible projects and alignment between Figma libraries and production implementations. Team capability: Improvement in design craft, Shopify knowledge and autonomous discovery and presentation delivery. Standalone design performance: Contribution to qualified opportunity wins, commercially sound scoping and successful delivery, assessed jointly with Sales. AI workflow impact: Validated improvements in cycle time, quality or cost, considered alongside adoption, rework and tooling expenditure. Research and optimisation outcomes: Evidence that customer findings inform decisions and that agreed hypotheses are evaluated. Conversion and related commercial outcomes will be assessed jointly with the wider team. Unlimited paid #J-18808-Ljbffr

Salary: Up to £100,000 Location: Gateshead Hybrid: 1-2 days per week in the office An established, product-led technology business is investing in AI, with an ambitious roadmap of new features and capabilities planned across its platform. The platform is already making a meaningful difference to people's everyday lives, with technology playing a central role in delivering valuable, personalised experiences. The next stage of development will focus on using AI to make the product even more intelligent, accessible and effective for its users. This creates an opportunity for a Lead AI Engineer to take ownership of AI development, shape the technical direction and establish AI engineering capability across the organisation. Working alongside an experienced engineering team, the position combines hands‑on development with technical leadership, taking AI-powered features from initial concept through to production. Rather than joining an established AI function, there's genuine scope to influence architecture, introduce engineering standards and help shape how AI is developed and delivered across the business. The role will involve making technical decisions around LLM integration, retrieval systems, model selection and wider system architecture, ensuring solutions are reliable, scalable and commercially viable. There will also be a strong focus on AI evaluation, monitoring, security and cost management, alongside mentoring existing engineers and helping develop their AI capabilities. This is a hands‑on technical leadership role without direct reports initially, offering the opportunity to lead AI development while remaining closely involved in engineering. • Strong software engineering background, ideally within backend or full-stack development., • Commercial experience designing, building and deploying AI/LLM-powered applications into production., • Experience integrating LLMs, APIs and retrieval systems into software products., • Strong understanding of AI architecture, including model selection, evaluation, reliability and performance., • Experience making technical decisions around scalability, infrastructure and cost., • Ability to take technical ownership, influence architectural decisions and mentor other engineers. Experience with RAG, tool calling, LLM orchestration and evaluation frameworks would be particularly relevant, alongside exposure to cloud AI services such as AWS Bedrock, Azure AI Foundry or Google Vertex AI. A background in TypeScript or Python would be useful, although the emphasis is on strong software engineering fundamentals and genuine experience delivering AI solutions rather than a specific programming language. #J-18808-Ljbffr

Archer is collaborating with Accenture to connect them with exceptional professionals for this role. Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK. Note: The above information relates to a specific client requirement You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solution in production, you have owned the evaluation harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle. This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. • Design and build production-grade agentic solutions end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability, • Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets, • Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management, • Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring, • Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases, design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs, • Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster, • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms, • Significant software engineering experience in production environments, • Hands‑on experience designing and deploying agentic AI solutions in a production environment — non‑negotiable, • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level, • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs, • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering, • LLMOps fundamentals: eval harness design, prompt versioning, and production observability, • Cloud‑native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm), • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience, • Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com We believe that no one should be discriminated against because of their differences.All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law.Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. #J-18808-Ljbffr

Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of what we do: • UK & Ireland's premier AWS, Microsoft & Oracle partner, • 4000+ strong, €450/£400m revenue business, • 10+ years as a Great Place to Work in Ireland & UK, • Best Workplace for Women in the UK & Ireland by GPTW, • Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you! AI is the biggest shift in how organisations build and work in a generation. The organisations who win will be the ones who can move beyond a working demo and get genuinely production‑grade, multi‑agent AI systems live, reliable and maintained at scale. That is the hardest part of the journey, and it's where this role sits. As an Applied AI Architect working in Version 1's Forward Deployed capability, you bring deep, hands‑on expertise in designing, building, deploying and maintaining agentic systems in production, and you bring it to customers as a trusted adviser, not from behind a desk. You've done this for real — not just prototyped an agent, but taken a multi‑agent architecture through the full lifecycle: design, orchestration, evaluation, deployment, and the unglamorous work of keeping it reliable once real users depend on it. You sit alongside customer architects and senior engineers, on their most technically demanding challenges, combining deep technical credibility with genuine consulting skill to shape decisions rather than simply hand over a design. This is a deeply technical role that lives in the room with the customer. You'll set the technical standard for Version 1's most complex agentic engagements, and you'll do it through influence and trust as much as through the strength of your own architecture. • Advise the customer's own AI architects. Act as the trusted technical adviser to the customer's AI architect and senior engineers, shaping their design and build decisions on agentic systems rather than owning delivery yourself., • Consult across the engagement. Run discovery, workshops and architecture reviews with customer stakeholders, translating technical trade‑offs into language that lands with both engineers and the business sponsors funding the work., • Architect multi‑agent systems, hands‑on. Work directly with customer engineering teams to co‑design multi‑agent architectures — orchestration, tool use, memory, routing and guardrails — for real production workloads., • Build reference implementations and accelerators. Create working prototypes, reference architectures, evaluation suites and accelerator code that customer teams take on and run themselves — proof that survives contact with production, not slideware., • Solve the hard production problems. Bring deep experience of what breaks agentic systems at scale — hallucination under load, tool‑call failures, runaway agent loops, latency and cost — and help customer teams design around it., • Set the technical bar for the engagement. Own the technical architecture and standards for Version 1's most complex agentic engagements, reviewing and pressure‑testing customer designs as a peer to their best architects., • Own evaluation and observability. Establish how a customer will know their agentic system is actually working — eval suites, tracing, guardrails and monitoring — before it goes anywhere near production., • Mentor on deep technical practice. Coach Applied AI Consultants and Associates on advanced AI engineering, sharing hands‑on expertise that goes well beyond the basics., • Build Version 1's technical IP. Contribute reusable architectures, patterns and accelerators to Version 1's shared toolkit, keeping it current with the frontier of agentic AI engineering., • Stay genuinely current. Track the latest agent frameworks, orchestration patterns and models closely enough to have a real, tested opinion on what's worth using and what isn't., • Proven agentic systems experience. You've personally designed, built, deployed and maintained multi‑agent systems in production — not a hackathon demo, a system real users depended on., • A genuine consultant, not just an engineer. You build trust quickly with customer stakeholders, read a room, and flex your style between hands‑on engineers and the people funding the work — this role lives in front of the customer, not behind a laptop., • Deep architectural credibility. You can design and defend a multi‑agent architecture — orchestration patterns, tool permissions, routing logic, guardrails — under scrutiny from a customer's best engineers., • Genuinely current technical depth. Your expertise in LLMs, agent frameworks and evaluation is real and current, built through hands‑on production work, not reading about it., • Comfortable in the hardest part of the job. You know that the interesting problems in agentic AI start after the demo works, and you're energised by solving them., • A builder who can advise, not just build. You'd rather be pairing on an architecture or debugging an agent trace than sitting in a status meeting, but you're just as effective guiding someone else's team to the right answer as reaching it yourself., • 10–15+ years in software engineering, including 5+ years designing and architecting systems., • A minimum of 2 years' hands‑on experience architecting and running AI/agentic systems in production., • A genuine track record of client‑facing or consulting work, advising engineering teams or technical stakeholders rather than only delivering internally., • Direct experience designing multi‑agent architectures: orchestration, tool use, memory, routing, guardrails and agent‑to‑agent communication., • Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols., • Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads., • Hands‑on experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production., • A degree in a related field, or equivalent practical experience., • A role built around the craft, in front of the customer. This track exists for people who want to stay deeply technical at the most senior level, advising and shaping rather than managing, without disappearing from client conversations., • The hardest, most interesting problems. You'll work on the agentic systems our most demanding customers are betting their operations on, at a stage of maturity most engineers never get to touch., • Real technical authority. You'll set the standard the rest of the team builds towards, earned through trust with customers as much as through the strength of your architecture., • Share in our success with our Quarterly Performance‑Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits, • Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme, • Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance, • Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme, • Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies, • Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat, • Reward schemes including Version 1’s Annual Excellence Awards & ‘Call‑Out’ platform., • Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. Version 1 is an equal opportunities employer. We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring including those shaped by disability and neurodiversity. Our employee‑designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth. #J-18808-Ljbffr

You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solution in production, you have owned the evaluation harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle (SDLC). This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. Architect and govern production-grade agentic solutions at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models Own LLMOps at programme scale: evaluation strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems Lead client engineering engagements at senior level — analyse the SDLC to identify AI/agentic opportunities and use cases, facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholders Extensive software engineering experience in production environments Hands‑on experience designing and deploying agentic AI solutions in a production environment — non‑negotiable Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud‑native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure People lead responsibilities: experience managing, developing, and performance‑managing a team of engineers; setting individual development plans and conducting career conversations #LI‑EU Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent‑and innovation‑led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360 value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360 value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. Bring your incredible skills and join our global team of innovators. We come together from different backgrounds across the world and work with the latest technologies to create value and growth for our clients. With us, you’ll continue to learn and grow so you can advance in your career. Your personal dreams and ambitions are just as important to us; that’s why we offer support any way we can—when you thrive, we all thrive. Explore your next step at Accenture Belong. Grow. Thrive. Join a great place to work for reinventors who drive meaningful change for our clients, communities, and the world. Wo rld. Explore your next step at Accenture #J-18808-Ljbffr

Our client is a global professional services and technology consultancy. Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK. Note: The above information relates to a specific client requirement You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solution in production, you have owned the evaluation harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle. This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. Key Responsibilities Design and build production-grade agentic solutions end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases, design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms Significant software engineering experience in production environments Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm) Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure #LI-EU About our client Our client is a leading global professional services company that helps the world's leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world's leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Engineering and Creative, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at Equal Employment Opportunity Statement We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. TPBN1_UKTJ

Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK. Note: The above information relates to a specific client requirement You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solution in production, you have owned the evaluation harness, and you know what happens when your agent fails at 2am because you have lived it. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle. This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. • Design and build production-grade agentic solutions end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability, • Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets, • Integrate and abstract across multiple LLM providers — OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management, • Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring, • Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases, design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs, • Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster, • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms, • Significant software engineering experience in production environments, • Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable, • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level, • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs, • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering, • LLMOps fundamentals: eval harness design, prompt versioning, and production observability, • Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm), • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience, • Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure #LI-EU #J-18808-Ljbffr

Job Description Job purpose:Our IT mission is to transform how data and AI are delivered to customers and colleagues around the world, with a focus on simplicity, trust, and measurable value. AI is central to this mission, providing tools and platforms for creating and operating secure, scalable data and AI solutions.Reporting to the BI and Analytics Manager, the Data Scientist is a valued member of the Enterprise Analytics & AI Hub. This role develops and evaluates advanced analytics, machine learning, and generative AI solutions that help us understand business challenges, improve decisions, and create better customer and colleague experiences.Using modern data science techniques and scalable AWS technologies, the Data Scientist connects business needs with reliable technical solutions. This role works closely with product, data engineering, software and platform engineering, security, governance, and domain experts to move ideas from discovery and experimentation into monitored production services.The Data Scientist plays a vital role within the Enterprise Analytics & AI Hub, contributing to the team's core objectives:• Turn ambiguous business questions into measurable data science problems, clear success measures, and evidence-based recommendations.• Build trusted models, data products, and AI capabilities in Nexus (our internal platform) that colleagues can use safely and effectively.• Improve the quality and usability of structured and unstructured data by making definitions, lineage, assumptions, and limitations clear.• Establish evaluation, observability, and feedback practices that improve accuracy, reliability, latency, and cost over time.• Foster a culture of responsible, data-informed experimentation by sharing insights, reusable approaches, and emerging techniques across the team.Key Responsibilities Key Responsibilities: Partner with product owners, domain experts, and stakeholders to translate business challenges into measurable analytical or AI outcomes, data requirements, and evaluation plans. Explore, prepare, and validate structured and unstructured data, establishing appropriate quality checks, feature definitions, lineage, and documented limitations. Design, develop, and validate statistical and machine learning solutions for tasks such as classification, regression, clustering, forecasting, segmentation, and optimization. Design experiments and apply statistical analysis, including A/B testing where appropriate, to measure impact, interpret uncertainty, and support sound decisions. Build and evaluate generative AI capabilities within Nexus (AWS stack), including prompt and context design, embeddings, retrieval-augmented generation, knowledge bases, and agent or tool behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation measures, using traces, token usage, cost, performance, and user feedback to improve solutions over time. Apply responsible AI, privacy, security, and data governance principles, with appropriate access controls, explainability, safety checks, and human oversight. Communicate insights, trade-offs, and recommendations clearly to technical and business audiences, and contribute reusable patterns, documentation, and learning across the team. #J-18808-Ljbffr

The Newcastle upon Tyne Hospitals NHS Foundation Trust is seeking an experienced and forward-thinking Consultant Clinical Neuropsychologist to provide clinical and professional leadership within Neuro Oncology, with a specialist focus on the Awake Craniotomy pathway. This senior role offers the opportunity to lead and shape a highly specialised neuropsychology service, supporting adults with brain tumours and epilepsy across the full surgical pathway--from pre-operative assessment and preparation, through intra-operative cognitive monitoring, to post-operative rehabilitation and outcome evaluation. The post holder will play a key role in ensuring the delivery of safe, effective and evidence-based care in a complex, high-risk neurosurgical context, while contributing to service development, governance, and strategic planning. We are looking for an individual with extensive post-qualification experience in neuropsychology within neurological or neurosurgical settings, who brings advanced, • Provide consultant-level clinical leadership for Neuro Oncology neuropsychology services, • Lead and oversee neuropsychological input into the Awake Craniotomy pathway, • Deliver expert consultation on complex cases involving cognition, capacity, communication and risk, • Develop and implement clinical pathways, protocols and competency frameworks, • Ensure services meet governance, safety and quality standards, • Line manage and supervise senior neuropsychology staff, supporting workforce development, • Lead audit, evaluation and outcome monitoring to inform service improvement, • Contribute to strategic planning, business cases and service development, • Work collaboratively with neurosurgery, oncology and multidisciplinary teams, • Support education, training and dissemination of specialist expertise expertise in complex assessment and intervention, alongside strong leadership skills and the ability to work collaboratively within multidisciplinary teams. The ideal candidate will be confident operating autonomously at consultant level, committed to maintaining high clinical standards, and motivated to drive innovation, workforce development and service improvement within a dynamic and evolving specialty. • As a flexible working friendly organisation, we want to be sure that you can work in a way that is best for us and for our patients, and for you. Speak to us about how we might be able to accommodate a flexible working arrangement. If it works for the service, we will do our best to make it work for you., • With around 2 million contacts with patients every year, we deliver care from:, • Royal Victoria Infirmary (RVI), • Freeman Hospital, • Newcastle Dental Hospital, • Cramlington Manor Walks, • Urgent treatment centres, • Newcastle Fertility Centre, • Northern Centre for Cancer Care, North Cumbria, • Northern Genetics Service, • These include a range of flagship services which deliver cutting-edge care (supported by state-of-the-art diagnostic services in both radiology and pathology) and are a catalyst for innovation to support pioneering clinical practice in the NHS. We also have offices at Regent Point in Gosforth and community sites. #J-18808-Ljbffr

Data sits at the heart of the company. This role ensures that Awin can fully leverage the data available across the group, enabling the development of advanced analytical and machine learning capabilities that support stronger commercial decision-making and enhance products used by client-facing teams. As a Senior Data Scientist, you will apply advanced statistical techniques, machine learning methods, and analytical approaches to solve complex business problems and deliver actionable insights that guide business strategy. Working across areas such as forecasting, recommendation systems, network intelligence, experimentation, and predictive modelling, you will lead the design, development, evaluation, and deployment of scalable solutions that create measurable business impact. You will work closely with business stakeholders, Product, Engineering, and Data teams to identify opportunities, shape problem definitions, and translate business challenges into practical, performance and business outcomes. Apply statistical modelling, machine learning, and advanced analytical techniques to solve complex business problems and generate actionable insights. Build scalable feature engineering, model development, and deployment workflows in collaboration with Data Engineering and Software Engineering teams. Drive rapid MVP development, validating ideas quickly while ensuring a path to sustainable production solutions. Define and promote best practices for model development, evaluation, monitoring, and governance. Mentor and support other data scientists, contributing to technical capability and knowledge sharing across the team. Communicate findings, recommendations, and technical concepts clearly to both technical and non-technical audiences. Contribute to the evolution of the Data Science roadmap, identifying new opportunities to apply advanced analytics and machine learning. Experience 5+ years of experience working as a Data Scientist, Machine Learning Engineer, Applied Scientist, or similar role. Proven experience delivering machine learning and analytical solutions from discovery through to deployment and business impact. Advanced proficiency in Python and relevant data science libraries, including NumPy, PySpark, Scikit-learn, TensorFlow, and/or PyTorch. Strong experience using Databricks, including Jobs, Asset Bundles, Delta Lake, and MLflow. Experience working with business stakeholders to define problems, scope solutions, and communicate outcomes effectively. Experience mentoring data scientists or providing technical leadership within a cross-functional team. Bachelor's degree or higher in Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related quantitative discipline. Our network of affiliate partnerships are diverse and transparent, as are the employees powering our vision to build the world's leading open partner ecosystem. We welcome all backgrounds, identities, and experiences. If you need support at any point in the application or interview process, please let us know. Awin is part of the Axel Springer group. Learn more at axelspringer.com/ en / , and explore the Axel Springer Essentials here: axelspringer.com/en/inside/the-essentials-what-we-have-adapted-and-why Technical solutions. You will be responsible for defining success metrics, establishing evaluation frameworks, and ensuring analytical solutions remain reliable, scalable, and aligned to business objectives. In this role, you will lead the development of end-to-end feature pipelines, models, and MVPs, balancing rapid experimentation with long-term sustainability. You will also provide technical leadership to other data scientists, contribute to best practices across the team, and help foster a collaborative, data-driven culture within the organisation. Lead the development and deployment of machine learning, forecasting, recommendation, and analytical solutions that create measurable business impact. Partner with stakeholders across Product, Commercial, Engineering, and Data teams to identify opportunities and translate business challenges into data-driven solutions. Design and implement robust evaluation frameworks, experiments, and success metrics to measure #J-18808-Ljbffr

Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK. Note: The above information relates to a specific client requirement You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle (SDLC). This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. • Architect and govern production-grade agentic solutions at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability, • Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable, • Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models, • Own LLMOps at programme scale: evaluation strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems, • Lead client engineering engagements at senior level — analyse the SDLC to identify AI/agentic opportunities and use cases, facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams, • Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements, • Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholders, • Extensive software engineering experience in production environments, • Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable, • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level, • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs, • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering, • LLMOps fundamentals: eval harness design, prompt versioning, and production observability, • Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm), • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience, • Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure, • People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations #J-18808-Ljbffr

Security Bid Manager Salary: £50,000 – £55,000 + OTE up to £85,000 Location: UK – Fully Remote An exciting opportunity has arisen for an experienced Security Bid Manager to join a growing organisation within the security services sector. This role is specifically suited to an experienced bid professional who has hands-on experience managing bids and tenders for security solutions and understands the full end-to-end bid process, from initial opportunity and bid/no-bid decisions through to solution development, stakeholder management, bid writing, commercial input, quality assurance and final submission. This is a highly collaborative and influential role, working side by side with senior management. You won't simply be handed a tender to manage — you'll have a genuine voice and say in the bid process, helping shape bid strategy, challenge opportunities, influence bid/no-bid decisions and determine how the organisation approaches each opportunity. It's also an exciting time to join the business, with the opportunity to help support its continued growth and play a role in developing the wider bid function and team. The Role As Security Bid Manager, you will take ownership of the full end-to-end bid lifecycle, ensuring submissions are accurate, compliant, commercially robust and focused on delivering a strong customer proposition. You will work closely with senior management, operational leaders and subject matter experts to assess opportunities, determine the best approach and develop credible, differentiated security solutions. Key responsibilities will include: Managing the complete bid and tender process for security solutions, from initial opportunity through to final submission. Working closely with senior management to assess opportunities and contribute to bid/no-bid decisions. Having a genuine voice in bid strategy, challenging opportunities and helping determine where the business should focus its efforts. Planning and coordinating multiple bids, ensuring deadlines, responsibilities and deliverables are clearly managed. Reviewing tender requirements and developing clear bid plans and response strategies. Leading tender kick-off meetings and coordinating internal bid teams and subject matter experts. Working alongside operational and commercial teams to develop credible, deliverable security solutions that meet customer requirements. Writing, editing and developing high-quality, compelling tender responses. Translating complex customer requirements into clear, customer-focused proposals. Challenging content, assumptions and proposed solutions where appropriate to strengthen the overall submission. Ensuring responses address customer requirements, evaluation criteria and agreed win strategies. Managing bid reviews, quality assurance and final submission checks. Ensuring submissions are compliant, accurate and supported by relevant evidence and case studies. Supporting pricing and commercial content to ensure accuracy and appropriate approvals. Maintaining bid libraries, approved content, case studies and supporting evidence. Supporting new business, retender and customer retention opportunities. Coordinating presentations, clarifications and post-tender activity where required. Monitoring tender outcomes, feedback and scoring to identify opportunities for continuous improvement. Producing tender reports and providing insight into bid activity, performance and outcomes. Contributing to the development and improvement of the wider bid function as the business continues to grow. About You Security sector bid management experience is essential. We are looking for someone who has direct experience managing bids and tenders for security solutions and who understands the full bid lifecycle, rather than having experience limited to bid writing or administration. You will ideally have: 2–3+ years' experience in security solutions bid management, ideally within a security services or closely related service-led organisation. Proven experience managing the full end-to-end bid process, from tender receipt and opportunity assessment through to bid/no-bid, solution development, writing, review, commercial input and final submission. A strong understanding of security services and security solutions, including the operational considerations involved in developing a deliverable customer proposition. Experience working with senior management, operational teams and subject matter experts. The confidence to challenge, influence and contribute to strategic bid decisions. Excellent bid writing, editing and proofreading skills. Commercial awareness and an understanding of how to translate operational solutions into customer value and competitive advantage. Experience managing multiple bids and competing deadlines. Strong attention to detail, accuracy and quality control. Experience managing bid governance, compliance and quality assurance. Experience using tender portals and/or bid management systems. Strong Microsoft Office skills, particularly Word, PowerPoint and Excel. APMP certification, or a willingness to work towards APMP, would be advantageous. What You'll Bring The successful candidate will be someone who can confidently own the entire bid process and understands what is required to turn a security tender opportunity into a high-quality, commercially compelling submission. You'll be someone who: Understands the operational solution behind the bid, not simply the written response. Can assess an opportunity and contribute meaningfully to bid/no-bid decisions. Is confident having a voice with senior management and can challenge constructively. Can develop a clear bid strategy and coordinate the right internal stakeholders. Can work with operational experts to develop realistic and deliverable security solutions. Identifies opportunities to differentiate the solution and demonstrate customer value. Produces persuasive, evidence-based bid responses. Manages reviews, quality assurance, compliance and submission deadlines. Builds strong relationships across senior management, commercial and operational teams. Remains organised and resilient when managing multiple bids and tight deadlines. Is commercially minded and understands what makes a security proposition competitive. Wants to be involved in building and developing the bid function as the organisation grows. The Opportunity This is more than a traditional bid-writing role. It's an opportunity for an experienced Security Bid Manager to work closely with senior management, have a genuine influence on the organisation's approach to new opportunities and play an important role in its continued growth. You'll have the autonomy to manage your own workload, the opportunity to contribute to bid/no-bid decisions and strategy, and the chance to help shape and develop the wider bid function and team as the business grows. New Ventures Recruitment is an equal opportunities employer and is acting as a recruitment agency for this vacancy. JBRP1_UKTJ

Our team covers all areas of transport planning, including transport strategy development, transport modelling and appraisal, feasibility studies, business case development, development planning, and monitoring and evaluation. Business Line:** Transportation. Developing and applying transport models

We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Strong attention to detail, with the patience to look and listen closely, and to replay or zoom in when something seems of

Grab your car, bike, motorbike, or scooter and be a delivery person whenever you want—for an hour, a weekend, or throughout the week. Have the right to work in the UK (and documents to support this). A smartphone (for navigation and delivery app use).

We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. We collect, retain and use personal data for our professional business purposes, including notifying you of opportunities

You decide how much or little you want to deliver and earn. Grab your car, bike, motorbike, or scooter and be a delivery person whenever you want—for an hour, a weekend, or throughout the week. Have the right to work in the UK (and documents to support this).

Comparing pairs of AI-generated images and videos and judging which one better follows the prompt. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. We collect, retain and

You decide how much or little you want to deliver and earn. Grab your car, bike, motorbike, or scooter and be a delivery person whenever you want—for an hour, a weekend, or throughout the week. Have the right to work in the UK (and documents to support this).

You decide how much or little you want to deliver and earn. Grab your car, bike, motorbike, or scooter and be a delivery person whenever you want—for an hour, a weekend, or throughout the week. Have the right to work in the UK (and documents to support this).

Grab your car, bike, motorbike, or scooter and be a delivery person whenever you want—for an hour, a weekend, or throughout the week. Have the right to work in the UK (and documents to support this). A smartphone (for navigation and delivery app use).