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DevOps / AI Engineer We are looking for a DevOps / AI Engineer with strong experience in modern DevOps practices and emerging GenAI-enabled engineering capabilities for our client (Global IT services and consulting company) and end client is a Bank . The ideal candidate will be responsible for delivering end-to-end software delivery lifecycle solutions while ensuring reliability, scalability, security, and compliance in enterprise environments. Role Focus • End-to-end software delivery lifecycle, • Infrastructure as Code (IaC), CI/CD, monitoring, and system reliability, • Strong understanding of enterprise environments, controls, and compliance requirements, • Ability to manage work and deliverables independently, • Ability to support GenAI-enabled engineering practices (e.g., AI-assisted development/operations) while adhering to enterprise governance, security, and risk controls Key Responsibilities • Design, implement, and maintain CI/CD pipelines (e.g., Jenkins), • Automate infrastructure provisioning and configuration (e.g., Ansible, Terraform), • Ensure high availability, scalability, and security of systems, • Collaborate with developers, QA, and IT operations to streamline releases, • Troubleshoot deployment, build, and infrastructure issues, • Maintain configuration management tools (Ansible), • Ensure compliance with enterprise controls and regulatory requirements, • Work independently to deliver on assigned tasks and projects, • Utilize Jira and Confluence for work tracking and documentation, • Enable and operationalise GenAI/LLM-based tooling in the DevOps toolchain (where approved), including secure access, environment configuration, and integration into CI/CD workflows, • Implement guardrails for GenAI usage (e.g., data handling, prompt/content logging where required, secrets protection, model/tool access controls) aligned to enterprise policies, • Support reliability and observability for GenAI-enabled services (e.g., monitoring latency, error rates, cost/usage, and drift/quality signals where applicable) Core Skills • Scripting/Programming: Bash, Python, Shell, • CI/CD Tools: Jenkins, GitLab CI, Azure DevOps, • Containerization: Docker, Kubernetes, • Infrastructure as Code: Ansible, Terraform, • Source Control: Git, Bitbucket, • Security & Compliance: Understanding of DevSecOps, secrets management, enterprise controls, and compliance, • Familiarity with Jira and Confluence, • GenAI/LLM Fundamentals: Understanding of LLM concepts (prompting, embeddings, RAG, model limitations), and how to apply them safely in engineering workflows, • GenAI Tooling & Integration: Experience using and integrating GenAI-assisted tools (e.g., code assistants, chat-based ops assistants) and/or APIs into developer/DevOps workflows, • Responsible AI & Data Handling: Awareness of privacy, IP, data classification, and secure usage patterns when working with GenAI tools in enterprise environments Preferred • Experience supporting GenAI platforms/services in production (e.g., model/API deployment patterns, prompt/version management, evaluation/monitoring, and cost controls) Ideal for someone who: Enjoys working independently, thrives in enterprise environments, and is passionate about combining DevOps with cutting-edge AI capabilities. 📩 Interested or know someone who fits? Feel free to reach out or apply! #Hiring #DevOps #AI #GenAI #PlatformEngineering #Cloud #Kubernetes #Terraform #Jenkins

Senior AI Engineer Sheffield - 1-2x week in office Salary: £80,000 - £90,000 This is an exciting opportunity to join a business that is investing heavily in AI and modern cloud technologies. You will play a key role in building AI‑driven products that have a direct impact on customer experience, operational efficiency and the future of their platform. The Company They are a tech‑forward insurance organisation with a strong focus on delivering smarter, more personalised digital products. Their teams combine data, engineering and customer expertise to create solutions that simplify complex challenges for their users. Innovation, collaboration and a flexible working culture are at the heart of how they operate. They continue to scale their AI capability and are looking for someone who can help shape this next phase of growth. The Role In this AI Platform Engineer role, you will: • Design, build and operate AI‑first products that deliver measurable value., • Develop and deploy production‑grade AI agents on GCP using ADK, integrating with internal systems via REST and JSON APIs., • Build and maintain robust evaluation and monitoring frameworks, including online and offline testing, A/B experiments and performance dashboards., • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations., • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP., • Embed security, compliance, GDPR controls and best‑practice engineering with clear documentation and stakeholder collaboration. Your Skills and Experience To be successful, you will bring: • Strong Python skills for backend services, SDKs, API development, authentication and testing., • Hands‑on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design., • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK., • Experience with document and data processing using tools such as Apache Tika, plus storage or caching technologies like Postgres, Redis, GCS or BigQuery., • Solid DevOps practices including CI/CD, Docker, observability and automated testing., • A product‑led mindset with a strong understanding of security, IAM, auditability and defining success metrics. What They Offer • Opportunities to shape AI products from the ground up., • A collaborative environment that encourages innovation and career progression. How to Apply If you are excited about building production‑ready AI systems and want to drive meaningful impact, please apply with your CV.

About Us: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L. Project Overview: As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go; evaluating and refining AI-generated code for efficiency, scalability, and reliability; and working with cross-functional teams to enhance enterprise-level AI-driven coding solutions. What Does a Typical Day Look Like? • Working on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go., • Evaluate and refine AI-generated code to ensure that it is efficient, scalable, and reliable., • Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks., • Build agents that can verify the quality of the code and identify error patterns., • Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them, • Design verification mechanisms that can automatically verify a solution to a software engineering task. Required Skills: • 3+ years of software engineering experience., • Strong expertise in building full-stack applications and deploying scalable, production-grade software using modern languages and tools., • Deep understanding of software architecture, design, development, debugging, and code quality/review assessment., • Excellent oral and written communication skills for clear, structured evaluation rationales. Engagement Details: • Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week (partial PST overlap required), • Type: Contractor (no medical/paid leave), • Duration: 1 month (starting next week; potential extensions based on performance and fit), • Location: Candidates must be based out of US, Canada or WEU countries (UK, Netherlands, Italy, Germany, …) Note: As part of assessments you will go through an AI video interview. After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile. Know amazing talent? Refer them at ___, and earn money from your network.

About Us: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L. Ideal Background: This role is ideal for engineers who have shipped high-impact products at fast-moving companies like Stripe, Airbnb, Cloudflare, Datadog, Coinbase, or similar high-growth engineering environments. We especially welcome graduates from programs with strong CS foundations such as University of Washington, University of Illinois Urbana-Champaign, UT Austin, University of Michigan, Purdue, and comparable institutions — though exceptional experience and skill always take precedence over pedigree. Project Overview: As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections across the full stack — in Python for backend and ML workflows, and JavaScript (React, Node.js) for frontend and API layers, alongside C/C++, Java, Rust, and Go. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions. What Does a Typical Day Look Like? • Work on AI model training initiatives by curating code examples, building solutions, and correcting code across both Python and JavaScript (React, Node.js), with additional work in C/C++, Java, Rust, and Go., • Evaluate and refine AI-generated code across backend and frontend contexts to ensure that it is efficient, scalable, and reliable., • Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks., • Build agents that can verify the quality of the code and identify error patterns across full-stack applications., • Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them., • Design verification mechanisms that can automatically verify a solution to a software engineering task. Required Skills: • Several years of software engineering experience (3 years or more), • Strong expertise in building full-stack applications using Python and JavaScript (React, Node.js), with the ability to work across backend and frontend codebases., • Experience deploying scalable, production-grade software using modern languages and tools., • Deep understanding of software architecture, design, development, debugging, and code quality/review assessment., • Excellent oral and written communication skills for clear, structured evaluation rationales. Engagement Details: • Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week, • Type: Contractor (no medical/paid leave), • Duration: 1 month (potential extensions based on performance and fit), • Location: Candidates must be based in the United States Evaluation Process: • The application process takes 15–30 minutes., • Completion of an AI video interview is required. Note: As part of assessments you will go through an AI video interview. After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile. Know amazing talent? Refer them at ___, and earn money from your network.

Senior AI Engineer (NLP / LLMs) – remote (UK based) £70-100k depending on experience A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments. The platform applies machine learning and large language models across complex, end-to-end data workflows, solving real-world problems with measurable social impact. The Role As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning outcomes, balancing experimentation with real-world delivery. What You’ll Be Doing • Designing and developing NLP and LLM-driven solutions for complex, real-world use cases, • Fine-tuning and adapting foundation models using domain-specific data, • Building evaluation frameworks, prompt testing tools and data preprocessing pipelines, • Monitoring, optimising and maintaining deployed models for performance, cost and reliability, • Implementing explainability, fairness and bias-mitigation strategies, • Collaborating on MLOps pipelines, CI/CD workflows and production deployments, • Mentoring junior engineers and promoting best practices across the team, • Staying current with advances in AI, NLP and MLOps to drive continuous improvement What We’re Looking For • Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership, • Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents), • Experience translating research and experimentation into production systems, • Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management, • Hands-on experience with Docker and Kubernetes, • Experience working in regulated or sensitive domains, • Exposure to graph-based retrieval techniques, • Experience with Azure ML and DevOps integrations

About Quantiphi: • Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI—driving measurable outcomes at the very core of their operations., • Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value—not just technology for technology’s sake., • Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact. We have been recognized with: • 3x AWS AI/ML award wins., • 3x NVIDIA Partner of the Year titles., • Recognized Leaders by Gartner, Forrester, IDC, ISG, Everest Group and other leading analyst and independent research firms., • We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators., • We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023. Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here! For more details, visit: ___ or ___. Role: MLOps Architect - AWS Experience Level: 8+ years Employment type: Full Time Location: Remote (UK) Description: • We are seeking an experienced MLOps/AIOps Architect who can drive end-to-end implementation of MLOps strategy and also contribute broadly across other enterprise AI/ML programs. This role demands a strong architectural mindset, hands-on technical depth, and the ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows., • The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, monitoring, automation and production-grade scalability patterns. Key Responsibilities: • Architect and implement the MLOps strategy for the programme, ensuring alignment with the project proposal and delivery roadmap., • Design and own enterprise-grade ML/LLM pipelines covering model training, validation, deployment, versioning, monitoring, and CI/CD automation., • Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.)., • Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems., • Serve as a technical authority across multiple internal and customer projects, contributing architectural patterns, best practices, and reusable frameworks., • Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems., • Define and implement standards for model deployment, monitoring, governance, and automation to ensure production-grade reliability and scalability., • Collaborate with cross-functional teams — data engineering, platform, DevOps, and client stakeholders — to deliver production-ready ML solutions., • Ensure all solutions adhere to security, governance, and compliance expectations, particularly around handling cloud services, Kubernetes workloads, and MLOps tools., • Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation across cloud-native ML platforms., • Mentor engineers and provide guidance on modern MLOps tools, platform capabilities, and best practices. Skills: • Expierence working in ML/AI engineering or MLOps roles with strong architecture exposure., • Strong experience in leading enterprise grade MLOps strategy and its execution., • Proven experience in implementing the adoption of enterprise-grade MLOps platforms with client data science teams., • Proven leadership in defining and executing enterprise MLOps strategy., • Demonstrated success in driving the adoption of enterprise-grade MLOps platforms with client data science teams., • Strong expertise in AWS cloud-native ML stack, including: SageMaker(primary), EKS, Lambda, API Gateway, CI/CD (CodeBuild/CodePipeline or equivalent)., • Hands-on experience with at least one major MLOps toolset and awareness of alternatives: MLflow, Kubeflow, SageMaker Pipelines, Airflow, BentoML, KServe, Seldon., • Deep understanding of model lifecycle management (feature engineering->training → registry → deployment → monitoring)., • Experience implementing or supporting LLMOps pipelines, including: prompt versioning, evaluation metrics, automation frameworks., • Deep understanding of ML lifecycle: data ingestion, feature engineering, training, evaluation, model packaging, CI/CD, drift detection, monitoring, and governance., • Strong experience with AWS SageMaker (Pipelines, Feature Store, Model Registry, Model Monitor)., • Experience implementing ML CI/CD pipelines including automated training, testing, validation, model promotion, and endpoint deployment., • Experience working on Infrastructure as Code (IaC) tools and CI/CD pipelines., • Experience with Kubernetes based development., • Experience with feature engineering pipelines and Feature Store management., • Understanding of lineage tracking: training data snapshot, feature versions, code versioning, metadata tracking, reproducibility., • Hands-on experience with AWS Bedrock and Agentcore service., • Experience with CloudWatch, SageMaker Model Monitor, Prometheus/Grafana., • Strong foundation in Python and cloud-native development patterns., • Solid understanding of security best practices, IAM, secrets management, and artifact governance. Nice to have: • Experience with vector databases, RAG pipelines, or multi-agent AI systems., • Exposure to DevOps and infrastructure-as-code (Terraform, Helm, CDK)., • Hands-on understanding of model drift detection, A/B testing, canary rollouts, and blue-green deployments., • Familiarity with Observability stacks (Prometheus, Grafana, CloudWatch, OpenTelemetry)., • SQL and data transformation experience using Snowflake, Databricks, Spark., • Ability to translate business goals into scalable AI/ML platform designs., • Strong communication and cross-team collaboration skills., • Ability to guide engineering teams through technical uncertainty and design choices. What is in it for you: • Make an impact at one of the world’s fastest-growing AI-first digital engineering companies., • Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues., • Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines., • Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.

Aveni is redefining how financial institutions use AI. We build real, production-ready agentic systems that reshape how banks, advisers and financial services firms operate, replacing fragmented processes with intelligent, end-to-end workflows. We have been recognised as Fintech of the Year for two consecutive years and awarded Best Specialist Technology Service at the Professional Adviser Awards 2025. Backed by leading investors including Puma Private Equity, and commercially supported by Lloyds Banking Group and Nationwide Building Society, we previously completed one of Scotland’s largest Series A rounds. Since then, we’ve continued to grow rapidly as adoption of AI in financial services accelerates, and we’re now scaling our team to meet that demand. The Role We’re looking for a Senior AI Engineer (FinLLM / NLP) to help drive the next generation of AI systems powering financial services. This role focuses on developing, fine-tuning and deploying advanced language models that operate at production scale within highly regulated environments. You’ll work alongside our NLP team, software engineers, and product leaders to build cutting-edge solutions that transform how financial organisations use AI. This is a hands-on role where you’ll shape both the technical direction and practical deployment of large language models and NLP systems within our platform. What You’ll Do • Build and optimise LLM-powered systems, • Architect, fine-tune and optimise machine learning models including LLMs and classical ML approaches, • Experiment with modern architectures such as Transformers and Mixture-of-Experts, • Apply efficient training and fine-tuning techniques including LoRA and parameter-efficient methods, • Develop robust evaluation approaches to measure model quality and reliability, • Develop scalable AI systems, • Build and deploy production-grade NLP pipelines and services, • Ensure models operate efficiently with low latency and high availability, • Integrate models into scalable cloud infrastructure and real-world applications, • Data strategy and model training, • Lead the acquisition, processing and governance of large structured and unstructured datasets, • Apply exploratory data analysis and validation techniques to improve training pipelines, • Ensure data privacy and governance standards suitable for financial services, • Engineering best practices, • Contribute to DevOps and MLOps pipelines, • Implement robust version control, testing and CI/CD workflows, • Support reliable deployment and monitoring of models in production environments, • Technical leadership, • Mentor engineers and contribute to the technical growth of the team, • Work closely with product, engineering and data teams to deliver AI solutions, • Stay at the forefront of AI and NLP research, applying new approaches where they add value What We’re Looking For Essential experience • Significant experience building, training and deploying machine learning models, • Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow, • Experience working with large-scale unstructured data, • Experience building and deploying production-ready NLP systems, • Familiarity with API integrations and data acquisition pipelines, • Experience implementing software engineering best practices including Git and agile development, • Experience working with cloud environments (preferably AWS) Nice to have • Experience with containerisation technologies such as Docker or Kubernetes, • Experience with frameworks such as vLLM or NeMo, • Knowledge of financial services NLP applications, • Experience designing evaluation methodologies for LLM outputs, • Experience building intelligent agents or multi-agent systems, • Skills and mindset, • Strong analytical problem-solving skills, • Ability to design scalable, production-ready AI systems, • Clear communication with both technical and non-technical stakeholders, • Passion for AI innovation and continuous learning, • Leadership and mentoring capability Qualifications • MSc or equivalent experience in a relevant field such as AI, Machine Learning, Computer Science, or Data Science Join Us in Making a Difference At Aveni, we believe that diversity drives innovation. We’ve built our business to ensure an inclusive workplace where everyone feels valued and empowered to contribute their best work. If you’re passionate about technology and its ability to drive positive change for the future of financial services, we’d love to hear from you. Even if you don’t meet 100% of requirements, we’d like to hear from you anyway if you believe you’d fit in. Apply now to join us on our mission to transform the financial services industry through AI. Benefits at Aveni What you’ll love: • Remote-first working across the UK, • Work abroad policy, • Co-working spaces available, • 34 days holiday (including flexible bank holidays) and your birthday off, • Company-wide off-sites, • Optional Personal Development Plan, • Flexible benefits platform, • Protection essentials including Life Insurance, Income Protection, Critical Illness cover, and Pension (up to 5% matched employer contribution with optional increased contributions), • Private health and dental care, • Potential share options, • Enhanced family leave

Venesky Brown Recruitment are currently looking for a Quality Management Lead to join work with the Sizewell C team. This role is a contract position (day rate) which can be based in Suffolk, London or Bristol offices, with hybrid working. Job Purpose / Overview: • The role of the Quality Management Lead (QML) is to ensure Sizewell C (SZC) Project quality requirements are complied with across the full project life-cycle (Contract award, Design, Procurement, Manufacture, Test, Shipping, Construction/Installation, Test/Commission and Contract close out)., • The primary purpose of the Quality Management Lead role is to ensure supply-chain adherence to the contracted quality assurance and quality control requirements. QMLs sit within the PDO Quality Team and are deployed to Programmes to serve this primary purpose. In so doing, day to day reporting is to the Quality Delivery Manager (QDM) who sets out their Programme quality requirements. This includes development and implementation of Project Quality Control Plans and associated inspection and surveillance activities., • Their secondary purpose is to support the PDO Quality Director, the Quality Delivery Manager and their programme in achieving adherence with the Integrated Management System arrangements, putting in place additional project-specific arrangements as required and managing quality for all activities within the scope of the programme. For a given portfolio of work, the Quality Management Lead is the single point of contact (SPOC) for all quality related elements associated with the supply chain. The QML will, on behalf of the Quality Delivery Manager, act as ‘Intelligent Customer’ in the capacity of ensuring that arrangements are in place, and effectively implemented by the supply chain, building on the lessons learned from the Hinkley Point C (HPC) project. Quality Management Leads will also support the Quality Delivery Manager and their respective Multi Discipline Team (MDTs) by the provision of quality management expertise to meet the quality requirements. This is to ensure products and/or services are provided Right First Time (RFT) in line with the SZC Project Goals, and in support of RFT, ensure effective resolution of issues and implementation of corrective actions to prevent recurrence. During manufacturing or construction, the Quality Management Lead shall, as ‘Intelligent Customer’, ensure that manufactured equipment or construction conforms to the contract design and technical specifications. The Quality Management Lead will work with inspection and surveillance bodies and the respective suppliers to ensure appropriate mechanisms and arrangements are in place to manage inspection and surveillance activities in the supply chain, and ensure appropriate inspection and surveillance is planned and executed commensurate with the associated risks. The Quality Management Lead shall also carry out their own surveillance on select manufacturing or construction documentation in accordance with the Surveillance Strategy and, where applicable, perform joint inspections with contracted inspection entities, in line with their own Surveillance Plans to oversee inspection performance. As part of demonstrating their ‘Intelligent Customer’ role, the QML shall measure and report quality metrics. to the project, Quality function and Supply Chain Management and perform regular audit of the supplier and the management of their sub-contractors to ensure supplier performance is maintained. Principal Accountabilities General • Support the development of quality (QA/QC) arrangements for deployment across the SZC organisation., • Implement key quality arrangements related to the following topics:, • Manage Quality Execution, • Support Technical Assessment of Suppliers, • Conduct Supplier Audit, • Conducting Manufacturing and/or Construction Surveillance, • Management of Non-Conformances, • Quality Release Certificate Process (where applicable);, • Undertake actions to resolve issues relating to the implementation of quality and to bring about improvements and support others in these actions. Primary accountability: • Review, accept and monitor Contractors Quality Assurance Plans (CQAP) provided by the supply chain., • Identify needs for supply chain audits, perform audits and resolve findings, • Produce Project Quality Control Plans (PQCP) for each contract/project, • In compliance with the PQCP, ensure deployment of key quality contractual arrangements including the General Quality Assurance Specification (GQAS), Lifetime Quality Records (LTQR) Specification, Quality Release Certificate and the Inspection & Test Plan Specification etc., • Provide relevant guidance to contractors, including contractor’s CQAPs, LTQR partitioning strategies and the arrangements for identifying and planning for Quality Related Activities, • Lead the implementation of LTQR reviews, • Support the determination and application of strategies for progressive provision of LTQRs by contractors., • Develop and maintain effective relationships with internal and external stakeholders including contracted inspection entities, • Ensure manufacturing and construction surveillance per contract is applied in a graded approach of safety function and project importance through surveillance offers and performance monitoring of the inspection agencies used, • Ensure overall effectiveness of ITPs submitted by the suppliers, checking that they are fit for purpose from a quality perspective and have been correctly distributed to the relevant internal parties for review and mark-up of the activities they wish to witness, • Where applicable, establish and check planned inspection witness and hold points marked in the supplier Inspection and Test Plans (ITP) / Quality Plans / Follow Up Documents (FUDs) and monitor their completion, • Coordinate, monitor and improve the efficiency of manufacturing documentation review and where applicable, inspection activities performed by contracted inspection entities, • Coordinate and lead the NNB review and acceptance of relevant manufacturing and construction documentation provided by contractors, • Perform joint inspections, surveillance and audit when required, • Support the monitoring and technical resolution of non-conformances including the management of corrections and corrective actions, • Support the review and acceptance of End of Manufacturing Reports (EoMR), End of Construction Status Reports (ECSR) and End of Erection Status Reports (EESR), • Responsible for the review and delivery of the end of manufacturing records, leading to the quality release of equipment to the SZC construction site, or handover of rooms/buildings/areas, • Produce quality documentation (e.g. specifications, procedures) as required. Secondary accountability: • Implement the quality execution plan within the Programme and undertaken reviews and checks to ensure quality is delivered by the supply chain efficiently and in accordance with programme quality requirements, • Identifying potential Quality issues before they arrive to enable mitigating actions, • Ensure supplier quality control requirements are adequately specified within contract documentation submitted in the Invitation To Tender (ITT), • Ensure quality management processes are correctly applied. Knowledge, Skills, Qualifications, Experience Essential • Position requires experience in project delivery, preferably in the nuclear power sector, with significant focus on project quality, with a solid understanding of the Quality Assurance and Quality Control in major projects across engineering, procurement, manufacturing, construction and commissioning., • A clear and considerable understanding of quality management best practice for deployment by large, complex and contract-led organisations., • knowledge of Quality Systems, ISO 9001, ISO 19443, IAEA GSR-2 and interrelated standards, • Confident and articulate communicator, able to prepare presentation material, and comfortable addressing individuals, small groups and very large audiences., • Able to support and implement practical solutions, whilst remaining open to the ideas of others., • Experience of interfacing with project teams and with supply chain organisations., • Analysis of data, preparing reports and making recommendations., • The ability to influence and to provide constructive challenge which is accepted by others., • The ability to build effective relationships with internal and external stakeholders. Desirable • Knowledge of the nuclear sector, ideally new build., • Knowledge & understanding of nuclear site license conditions., • Ability to speak French is advantageous., • Knowledge of pressure and nuclear codes, • Knowledge of Welding, Non Destructive Testing (NDT), Non-Destructive Evaluation (NDE) Qualifications & Experience • HNC/HND qualification or degree in a relevant science or engineering subject, or equivalent qualification., • Broad experience of implementing a variety of quality related solutions, • Proven track record of delivering results, • Proven leadership experience working in a quality assurance/control environment within the nuclear industry or other relevant safety critical industry., • Proven experience of interaction and resolving issues with a wide range of stakeholders in a multi cultural environment., • Experience performing supplier audits Desirable, • Hold a professional accreditation including IRCA certified auditor, • Corporate Member or working towards membership of the Chartered Quality Institute & Chartered Quality Professional, • Commercial exposure, especially supplier management, • Experience of interacting with regulators e.g. the ONR., • Knowledge of Improvement Methodologies, Tools & Techniques eg. Lean 6 Sigma

About Us: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L. Project Overview: As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go; evaluating and refining AI-generated code for efficiency, scalability, and reliability; and working with cross-functional teams to enhance enterprise-level AI-driven coding solutions. What Does a Typical Day Look Like? • Working on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, JavaScript (including ReactJS), C/C++, Java, Rust, and Go., • Evaluate and refine AI-generated code to ensure that it is efficient, scalable, and reliable., • Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks., • Build agents that can verify the quality of the code and identify error patterns., • Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them, • Design verification mechanisms that can automatically verify a solution to a software engineering task. Required Skills: • 3+ years of software engineering experience., • Strong expertise in building full-stack applications and deploying scalable, production-grade software using modern languages and tools., • Deep understanding of software architecture, design, development, debugging, and code quality/review assessment., • Excellent oral and written communication skills for clear, structured evaluation rationales. Engagement Details: • Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week (partial PST overlap required), • Type: Contractor (no medical/paid leave), • Duration: 1 month (starting next week; potential extensions based on performance and fit), • Location: Candidates must be based out of US, Canada or WEU countries (UK, Netherlands, Italy, Germany, …) Note: As part of assessments you will go through an AI video interview. After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile. Know amazing talent? Refer them at ___, and earn money from your network.

Accelerant is seeking a Product Area Lead Architect to provide hands on, operational architectural leadership for our Insights, Analytics & Workflows product area. This role operates at a Principal level, influencing architecture and execution across multiple autonomous product teams. You will work closely with team architects, engineering managers, product managers, and Data Science teams to ensure teams move fast without fragmenting the architecture. This is not an ivory tower architecture role. It is highly collaborative, pragmatic, and operational, focused on identifying architectural gaps, managing dependencies, and enabling teams to execute confidently within a shared architectural framework. You will champion standards based architecture, leveraging web standards, open protocols, and industry conventions to build interoperable, accessible, and future proof systems. Key Responsibilities Operational Architectural Leadership • Ensure architectural alignment across product teams, partnering closely with team architects and engineering managers, • Proactively identify architectural gaps, technical debt, and quality risks; drive resolution through collaboration and influence, • Manage cross team technical dependencies to enable independent, parallel execution, • Translate architectural strategy into clear, actionable guidance that teams can apply sprint by sprint Cross Team Coordination & Alignment • Facilitate architectural discussions and resolve technical conflicts across teams through principled, pragmatic decision making, • Act as an escalation point for complex cross team technical challenges, • Ensure architectural decisions are clearly communicated, understood, and consistently applied Design and Innovation • Define and maintain architectural patterns across backend services, APIs, data platforms, and front end systems, • Design scalable, resilient systems for analytics, workflow orchestration, and intelligence features, • Guide decomposition of legacy systems into well defined services and domains, • Evaluate technologies and data stores, favoring open standards and long term maintainability, • Architect distributed systems with focus on reliability, fault tolerance, and scalability Standards & Governance • Establish API design standards ensuring consistency, discoverability, and ease of integration, • Define front end standards prioritizing web platform capabilities, progressive enhancement, and accessibility (WCAG), • Create governance frameworks that balance standardization with team autonomy, • Drive adoption of industry standards (OAuth2, OpenID Connect, OpenTelemetry, JSON:API) over proprietary alternatives Technical Leadership • Partner with engineering teams on design reviews, PR reviews, and implementation guidance, • Establish standards for cross cutting concerns: API versioning, auth, observability, error handling, and resiliency patterns, • Collaborate with platform and DevOps teams on containerization, CI/CD, and cloud native deployment, • Produce clear technical design documentation that drives alignment and knowledge sharing, • Mentor engineers and raise the overall architectural maturity of the organization GenAI, ML & AI Architecture • Architect customer facing GenAI features using LLMs, including RAG pipelines, prompt engineering frameworks, and conversational AI interfaces, • Define patterns for ML model integration: serving endpoints, API contracts, versioning, and health monitoring, • Partner with Data Science to translate models into production grade features with clear integration contracts and deployment workflows, • Establish standards for responsible AI, including evaluation criteria, privacy guardrails, and LLM output validation AI Transformation & Productivity Leadership • Scale AI driven development workflows across teams, ensuring engineers leverage AI coding tools effectively, • Guide team architects and coach senior engineers on using AI tools to enhance productivity and code quality, • Work hands on with teams to identify opportunities for AI to solve operational challenges and improve velocity Solution Evaluation & Quality Assurance • Evaluate and recommend technologies to enhance capabilities across analytics, workflow, and intelligence domains, • Ensure architectural integrity through code reviews, assessments, and continuous monitoring, • Proactively identify technical risks and devise strategies for reliability, security, and performance Technical Requirements Full Stack SaaS Architecture: • Strong proficiency in modern JavaScript/TypeScript and Node.js, • Deep knowledge of web platform fundamentals and browser native capabilities, • Experience designing and evolving well structured APIs for platform integrations Architectural & Systems Thinking: • Deep knowledge of architecture principles, design patterns, and distributed systems, • Proven ability to make pragmatic tradeoffs in complex, evolving systems, • Experience in cloud native environments, preferably AWS AI Enabled Engineering: • Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, Claude, etc.), • Understanding of AI applications for development productivity and code quality improvement Qualifications • 8 to 12+ years in software engineering and architecture roles, • Proven experience operating across multiple agile teams in an architectural leadership capacity, • Track record of managing cross team dependencies and bridging architectural vision with day to day execution, • Proven ability to drive AI adoption and transformation within engineering organizations, • Excellent communication and facilitation skills with ability to align work across distributed teams, • Pragmatic, operational mindset with strong problem solving abilities, • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Learning & Development Partner Hybrid working (office/home based) Healthcare / regulated environment A well-established organisation operating within a regulated healthcare environment is seeking an experienced Learning & Development Partner to lead learning and development across a defined operational region. This is a highly visible, consultative role, working closely with senior operational and clinical leaders to ensure learning activity is strategically aligned, risk-based and delivers measurable improvements in capability, performance and care quality. The Role As Learning & Development Partner, you will act as the strategic owner of learning within your region, partnering with Operations Directors, Regional Service Directors and local leadership teams to deliver impactful, future-focused learning solutions. Key elements of the role include: • Owning and delivering a single, integrated regional learning plan aligned to clinical, operational and regulatory priorities, • Providing professional L&D consultancy to senior stakeholders, • Driving consistency, discipline and quality in learning delivery across multiple sites, • Feeding regional insight into central L&D strategy and curriculum development Key Responsibilities Regional Learning Planning & Alignment • Develop and maintain a regionally owned annual learning plan aligned to:, • clinical and operational priorities, • workforce risks and capability gaps, • statutory, mandatory and regulatory requirements, • Work with senior operational, quality and clinical stakeholders to prioritise learning needs, • Ensure plans are realistic, resourced and risk-based Monitoring, Evaluation & Performance Improvement • Track delivery against the learning plan and escalate risks to completion, • Evaluate learning quality and impact using feedback, compliance data, competence assessments and training matrices, • Identify performance trends and recommend improvements or changes to delivery approach Quality Assurance of Training Delivery • Observe learning delivery to assess quality, accuracy, consistency and effectiveness, • Provide coaching and developmental feedback to facilitators and trainers, • Ensure learning is delivered by appropriately skilled and competent facilitators Learning Strategy & Insight • Provide insight to central L&D on curriculum gaps, outdated content and emerging needs, • Represent regional risks, priorities and opportunities within central L&D forums Stakeholder Engagement • Act as the primary L&D contact for senior regional stakeholders, • Build strong working relationships across Operations, Quality, Clinical, HR and L&D teams, • Act as a connector between regional operations and the central L&D function Reporting, Insight & Risk Management • Produce concise, insight-led reports covering progress, risks, capability gaps and compliance issues, • Ensure learning data is accurate, reliable and triangulated with workforce and performance data, • Implement and monitor evaluation frameworks to demonstrate learning impact About You You will be a confident and credible L&D professional with experience operating in complex or regulated environments, ideally within healthcare. Essential skills and experience: • CIPD Level 5 in Learning & Development (or equivalent), • Strong understanding of adult learning principles and instructional design, • Experience of L&D governance, compliance frameworks and Learning Needs Analysis, • Proven experience delivering both clinical and non-clinical learning solutions, • Strong stakeholder management and influencing capability, • Experience leading L&D initiatives across multiple sites or regions, • Proven ability to evaluate learning impact and drive continuous improvement, • Strong analytical and reporting skills, • Confident use of LMS platforms and digital learning tools, • Coaching and mentoring capability Desirable: • Hybrid working model, • Flexibility required around working hours and travel, • UK driving licence required where applicable, • Pre-employment checks will be required, • Strong commitment to safeguarding, health & safety, and equality, diversity & inclusion This role offers the opportunity to make a tangible impact on workforce capability, learning quality and organisational performance within a values-led, regulated environment. Apply directly to be considered or email

About Us: Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L. Ideal Background: This role is ideal for engineers who have worked at the frontier of AI — at companies like OpenAI, NVIDIA, Databricks, Palantir, Snowflake, or similar organizations pushing the boundaries of intelligent systems. We especially welcome graduates from leading programs such as Harvard, Columbia, Princeton, Yale, University of Pennsylvania, and comparable institutions — though exceptional experience and skill always take precedence over pedigree. Project Overview: As a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS) — with particular emphasis on systems-level code, performance-critical applications, and infrastructure. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions. What Does a Typical Day Look Like? • Work on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS)., • Evaluate and refine AI-generated code with an emphasis on systems-level correctness, performance, and reliability., • Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks., • Build agents that can verify the quality of systems-level and infrastructure code and identify error patterns., • Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them., • Design verification mechanisms that can automatically verify a solution to a software engineering task. Required Skills: • Several years of software engineering experience (3 years or more), • Strong expertise in systems programming, infrastructure, or backend development using languages like Python, C/C++, Rust, and Go., • Experience building and deploying scalable, production-grade software using modern languages and tools., • Deep understanding of software architecture, design, development, debugging, and code quality/review assessment., • Excellent oral and written communication skills for clear, structured evaluation rationales. Engagement Details: • Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week, • Type: Contractor (no medical/paid leave), • Duration: 1 month (potential extensions based on performance and fit), • Location: Candidates must be based in the United States Evaluation Process: • The application process takes 15–30 minutes., • Completion of an AI video interview is required. Note: As part of assessments you will go through an AI video interview. After applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile. Know amazing talent? Refer them at ___, and earn money from your network.

Job Title: Project Lead - (SEND Reform Plan) Location: South Yorkshire (Hybrid - 1-2 days onsite per week) Contract duration: 2-3 months initially Start Date: ASAP Day Rate: £450+ per day We are currently supporting a local authority in South Yorkshire with the recruitment of a Project Lead - SEND Reform Plan. This is a key interim role focused on leading the development of a Local Area SEND Improvement Plan, bringing together existing documentation, data, and partner insight into a clear, structured and deliverable strategic improvement plan. The successful candidate will work across education, health, and social care partners to ensure alignment with statutory requirements and local priorities, while translating complex information into a coherent and actionable framework. Key responsibilities: Lead the development of a comprehensive SEND Area Improvement Plan, ensuring alignment with statutory requirements and local strategic objectives Collate, review and integrate key documents including: SEND Self-Evaluation Framework (SEF) SEND service performance and monitoring data Finance plans and datasets covering the past five years Relevant transformation and service strategies Engage effectively with partners across education, health, social care, and parent/carer representatives Facilitate collaboration and shared ownership of the improvement plan across stakeholders Translate a wide range of documentation, feedback and evidence into structured planning templates Manage timelines to ensure delivery of a final plan by 19th June Provide regular progress updates and clear recommendations throughout the processEssential skills & experience: Strong knowledge of SEND systems and local area improvement frameworks Proven experience producing strategic or area improvement plans, ideally within a local authority setting Ability to interpret and synthesise complex information from multiple sources Strong stakeholder engagement and partnership working experience Excellent analytical, organisational, and written communication skills Ability to work independently and manage delivery with minimal supervisionIf you are interested in this opportunity, please apply with an updated CV, and I will be in touch to discuss further. Sellick Partnership is proud to be an inclusive and accessible recruitment business and we support applications from candidates of all backgrounds and circumstances. Please note, our advertisements use years' experience, hourly rates, and salary levels purely as a guide and we assess applications based on the experience and skills evidenced on the CV. For information on how your personal details may be used by Sellick Partnership, please review our data processing notice on our website