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About the Role We're looking for a Full Stack .NET Developer to join our growing Development team at StoneShot. This is a great opportunity for a mid-level developer who wants to take ownership of features, contribute to technical decisions, and build high-quality applications used by leading financial services brands. You'll be working across the full stack, helping to design and deliver secure, scalable, and user-friendly digital products. You'll collaborate closely with developers, designers, and stakeholders, playing a key role in shaping what we build and how we build it. You’ll also have the opportunity to work with modern AI-assisted and agentic approaches within the software development lifecycle as part of our evolving engineering practices. What You'll Be Doing • Designing, building, and maintaining full-stack solutions, • Developing new features from concept through to delivery, • Writing clean, maintainable, and scalable code, • Collaborating with cross-functional teams to deliver high-quality solutions, • Troubleshooting and optimising existing systems, • Participating in code reviews and supporting junior developers where appropriate Tech & Skills (Essential) • ~4+ years' experience in software development, • Strong experience with C# and .NET (MVC / .NET), • Experience working with SQL Server and relational databases, • Solid understanding of HTML, CSS, and modern web development practices, • Strong grasp of object-oriented programming principles, • Problem-solving mindset and attention to detail Nice to Have • Commercial experience using agentic AI or AI-assisted tooling within the software development lifecycle, • Experience with Entity Framework or similar ORM tools, • Exposure to JavaScript frameworks, • Familiarity with Azure / Azure DevOps / CI/CD pipelines, • Experience working with or modernising legacy systems, • Understanding of performance optimisation and scalable architecture What You'll Get • Competitive salary based on experience, • 22 days holiday + bank holidays, increasing with service, • Additional time off over Christmas and New Year, • Remote-first working (with occasional office time), • Pension scheme and wellbeing support (including eye care), • Ongoing training and development opportunities Location Remote (UK-based) with occasional travel to Stevenage, Hertfordshire. Eligibility Applicants must have the right to work in the UK (we are unable to offer sponsorship for this role). StoneShot is an equal opportunities employer. We are committed to creating an inclusive environment and welcome applications from all suitably qualified individuals. About StoneShot StoneShot is a digital marketing technology and services provider specialising in financial services. We help marketing teams at banks and financial institutions improve engagement, streamline operations, and deliver better client experiences. Our clients range from fast-growing boutique firms to global organisations including BNP Paribas, HSBC, and UBS. Founded in London in 2001, we now operate globally with offices in London, New York, and Singapore, supporting clients in over 25 countries.

Support and mentor junior developers. We’re looking for an experienced Senior/Lead Developer to join our Resident Experience product team. You’ll work across the full software development lifecycle, helping shape the vision and architecture of the platform, writing clean, maintainable code, and

As part of our Group AI Team, we are scaling our internal capabilities to deliver cutting-edge, production-grade AI solutions across our global operations. We are establishing an "Agentic Factory" - a dedicated, high-velocity delivery team focused on designing, building, and deploying genAI & ML solutions, multi-agent workflows, and automation systems to solve complex business problems. The primary goals of the team include: • Leading the technical design and architecture of AI solutions, in addition to building and running an AI platform to deliver business-specific Use Case solutions., • Collaborating with the Data Platform to team in ingesting and transforming data from multiple systems, modeling data, and engineering data marts to create reusable data assets, including developing and implementing machine learning models, genAI, and Agentic AI., • Creating an operating a company wide agentic AI solution platform to help scale up AI capabilities across all functions and regions., • Building AI models and a data science platform that enables Rentokil to derive significant value from AI, from machine learning to gen AI and beyond, and ensuring the quality and reliability of AI solutions deployed on the platform., • Support, govern and enable company-wide adoption of emerging AI technologies. We are seeking a pragmatic, highly technical individual to lead the engineering efforts within our Agentic Factory. Sitting directly alongside our AI Delivery Manager and AI Product Owner, you will bridge the gap between business requirements and technical execution. Together with the AI & Data Architect, you will provide architectural oversight, defining engineering best practices, and mentoring a talented team of AI engineers & Data Scientists, while remaining hands-on enough to solve complex engineering bottlenecks; You will support Use Case Design and feasibility assessments, ensuring opportunities explored are achievable and scalable. You will support the Head of Engineering as the execution arm for AI responsibilities, extending your focus beyond the AI team to support and enable other IT teams across the organisation. • Design Agentic Systems: Design and scale robust, secure, and production-ready multi-agent workflows, orchestrations, and advanced RAG architectures, in collaboration with Enterprise Architecture principles. Drive delivery by designing and building agentic solutions, spanning from piloting to full implementation, • Define Engineering Excellence: Establish strict coding standards, code review processes, testing frameworks, and evaluation metrics for generative AI applications. Support and strictly enforce the standards set by the Head of Engineering and Technical Architect, • Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost-effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines., • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise-grade safety, security, and compliance., • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise-grade safety, security, and compliance., • Internal AI Enablement & Prompt Lifecycle: Manage the engineering workflows, CI/CD pipelines, version control, and evaluation frameworks for internal developer-facing AI assets, including prompt libraries and automated testing agents., • Grow the team: Act as a technical mentor to a team of intermediate and junior AI Engineers, fostering a culture of continuous learning, clean code, and agility., • Pragmatic Delivery: Collaborate with the AI Product Owner and Business Analysts to translate abstract business use cases into structured, achievable technical sprints., • Drive MVP to Production: Shift the team’s focus from sandboxed proof-of-concepts (PoCs) to reliable, resilient applications deployed to production for global users, leading AI engineering for AI team solutions and actively supporting junior engineers through this transition., • Support the company’s evolving AI strategy, providing an expert voice on Use Case identification, platform identification and tool selection., • Advise the AI portfolio Lead in scaling impact and AI capability across the company, beyond the Group AI Team., • Stay up to date on market trends, new opportunities, and the changing landscape of AI technologies. Expert-level experience building complex LLM-powered systems and multi-agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Deep practical understanding of machine learning algorithms, natural language processing (NLP) techniques, and the optimization of large language models for enterprise deployment. Strong proficiency in designing optimized ELT/ETL pipelines and managing data lake/data warehouse architectures. Hands-on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/Vertex AI Pipelines). Extensive experience leading technical delivery, defining engineering milestones, running code reviews, and successfully mentoring junior or intermediate engineering talent. Works with high autonomy under broad strategic guidance. Accountable for defining and meeting technical, architectural, and delivery goals, establishing milestones, and assigning tasks. Exerts major technical influence across the organization, partners, and peers. Partners with cross-functional business and product leaders, making key architectural decisions that affect budgets, timelines, and scalability. Manages diverse, highly complex, and unpredictable technical challenges. Uses fundamental engineering principles to connect cutting-edge AI research with practical enterprise software. Advises executives on AI trends, risks, and tools. Bridges the gap between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. • Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code., • SQL: Expert querying, database design, partitioning, and optimization strategies for large-scale BigQuery environments., • Google Cloud Certified Cloud Engineer, • Google Cloud Certified Professional Data Engineer / Cloud AI Engineer, • Competitive salary and bonus scheme, • Hybrid working, • Rentokil Initial Reward Scheme, • 23 days holiday, plus 8 bank holidays, • Employee Assistance Programme, • Death in service benefit, • Healthcare, • Free parking At Rentokil Initial, our customers and colleagues represent diverse backgrounds and experiences. We take pride in being an equal opportunity employer, actively encouraging applications from individuals from all walks of life. Our belief is that everyone irrespective of age, gender, gender identity, gender expression, ethnicity, sexual orientation, disabilities, religion, or beliefs, has the potential to thrive and contribute. We embrace the differences that make each of our colleagues unique, fostering an inclusive environment where everyone can be their authentic selves and feel a sense of belonging. To ensure that your journey with us is accessible if you have any individual requirements we invite you to communicate any specific needs or preferences you may have during any stage of the recruitment process. Our team is available to support you; feel free to reach out to () if you need anything #J-18808-Ljbffr

As part of our Group AI Team, we are scaling our internal capabilities to deliver cutting‑edge, production‑grade AI solutions across our global operations. We are establishing an "Agentic Factory" - a dedicated, high‑velocity delivery team focused on designing, building, and deploying genAI & ML solutions, multi‑agent workflows, and automation systems to solve complex business problems. • Leading the technical design and architecture of AI solutions, in addition to building and running an AI platform to deliver business‑specific Use Case solutions., • Collaborating with the Data Platform to team in ingesting and transforming data from multiple systems, modeling data, and engineering data marts to create reusable data assets, including developing and implementing machine learning models, genAI, and Agentic AI., • Creating an operating a company wide agentic AI solution platform to help scale up AI capabilities across all functions and regions., • Building AI models and a data science platform that enables Rentokil to derive significant value from AI, from machine learning to gen AI and beyond, and ensuring the quality and reliability of AI solutions deployed on the platform., • Support, govern and enable company‑wide adoption of emerging AI technologies. We are seeking a pragmatic, highly technical individual to lead the engineering efforts within our Agentic Factory. Sitting directly alongside our AI Delivery Manager and AI Product Owner, you will bridge the gap between business requirements and technical execution. Together with the AI & Data Architect, you will provide architectural oversight, defining engineering best practices, and mentoring a talented team of AI engineers & Data Scientists, while remaining hands‑on enough to solve complex engineering bottlenecks; You will support Use Case Design and feasibility assessments, ensuring opportunities explored are achievable and scalable. You will support the Head of Engineering as the execution arm for AI responsibilities, extending your focus beyond the AI team to support and enable other IT teams across the organisation. • Design Agentic Systems: Design and scale robust, secure, and production‑ready multi‑agent workflows, orchestrations, and advanced RAG architectures, in collaboration with Enterprise Architecture principles. Drive delivery by designing and building agentic solutions, spanning from piloting to full implementation, • Define Engineering Excellence: Establish strict coding standards, code review processes, testing frameworks, and evaluation metrics for generative AI applications. Support and strictly enforce the standards set by the Head of Engineering and Technical Architect, • Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost‑effective model deployment via Vertex AI and containerised environments. Take ownership of building and maintaining robust LLMOps pipelines., • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise‑grade safety, security, and compliance., • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise‑grade safety, security, and compliance., • Internal AI Enablement & Prompt Lifecycle: Manage the engineering workflows, CI/CD pipelines, version control, and evaluation frameworks for internal developer‑facing AI assets, including prompt libraries and automated testing agents., • Grow the team: Act as a technical mentor to a team of intermediate and junior AI Engineers, fostering a culture of continuous learning, clean code, and agility., • Pragmatic Delivery: Collaborate with the AI Product Owner and Business Analysts to translate abstract business use cases into structured, achievable technical sprints., • Drive MVP to Production: Shift the team’s focus from sandboxed proof‑of‑concepts (PoCs) to reliable, resilient applications deployed to production for global users, leading AI engineering for AI team solutions and actively supporting junior engineers through this transition., • Support the company’s evolving AI strategy, providing an expert voice on Use Case identification, platform identification and tool selection., • Advise the AI portfolio Lead in scaling impact and AI capability across the company, beyond the Group AI Team., • Stay up to date on market trends, new opportunities, and the changing landscape of AI technologies. AI Orchestration & Development: Expert-level experience building complex LLM‑powered systems and multi‑agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural language processing (NLP) techniques, and the optimization of large language models for enterprise deployment. Data Engineering & Cloud Computing: Strong proficiency in designing optimized ELT/ETL pipelines and managing data lake/data warehouse architectures. Hands‑on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). MLOps/LLMOps Pipelines: Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerised workflows using Docker and Kubernetes (GKE/Vertex AI Pipelines). Team Leadership & Mentorship: Extensive experience leading technical delivery, defining engineering milestones, running code reviews, and successfully mentoring junior or intermediate engineering talent. Autonomy: Works with high autonomy under broad strategic guidance. Accountable for defining and meeting technical, architectural, and delivery goals, establishing milestones, and assigning tasks. Influence: Exerts major technical influence across the organization, partners, and peers. Partners with cross‑functional business and product leaders, making key architectural decisions that affect budgets, timelines, and scalability. Complexity: Manages diverse, highly complex, and unpredictable technical challenges. Uses fundamental engineering principles to connect cutting‑edge AI research with practical enterprise software. Business Skills: Advises executives on AI trends, risks, and tools. Bridges the gap between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‑solving. • Python: Advanced, production‑grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code., • SQL: Expert querying, database design, partitioning, and optimization strategies for large‑scale BigQuery environments. Desirable: • Google Cloud Certified Cloud Engineer, • Google Cloud Certified Professional Data Engineer / Cloud AI Engineer Degree Qualification or Equivalent: A Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a highly quantitative field is desirable; however, a proven track record of architecting and shipping production‑grade commercial AI systems is highly valued and may substitute for specific academic credentials. IT HNC/HND courses will also be accepted. • Competitive salary and bonus scheme, • Hybrid working, • Rentokil Initial Reward Scheme, • 23 days holiday, plus 8 bank holidays, • Employee Assistance Programme, • Death in service benefit, • Healthcare, • Free parking At Rentokil Initial, our customers and colleagues represent diverse backgrounds and experiences. We take pride in being an equal opportunity employer, actively encouraging applications from individuals from all walks of life. Our belief is that everyone irrespective of age, gender, gender identity, gender expression, ethnicity, sexual orientation, disabilities, religion, or beliefs, has the potential to thrive and contribute. We embrace the differences that make each of our colleagues unique, fostering an inclusive environment where everyone can be their authentic selves and feel a sense of belonging. To ensure that your journey with us is accessible if you have any individual requirements we invite you to communicate any specific needs or preferences you may have during any stage of the recruitment process. Our team is available to support you; feel free to reach out to if you need anything #J-18808-Ljbffr

As part of our Group AI Team, we are scaling our internal capabilities to deliver cutting-edge, production-grade AI solutions across our global operations. We are establishing an "Agentic Factory" - a dedicated, high-velocity delivery team focused on designing, building, and deploying genAI & ML solutions, multi-agent workflows, and automation systems to solve complex business problems. The primary goals of the team include: • Leading the technical design and architecture of AI solutions, in addition to building and running an AI platform to deliver business-specific Use Case solutions, • Collaborating with the Data Platform to team in ingesting and transforming data from multiple systems, modeling data, and engineering data marts to create reusable data assets, including developing and implementing machine learning models, genAI, and Agentic AI, • Creating an operating a company wide agentic AI solution platform to help scale up AI capabilities across all functions and regions, • Building AI models and a data science platform that enables Rentokil to derive significant value from AI, from machine learning to gen AI and beyond, and ensuring the quality and reliability of AI solutions deployed on the platform, • Support, govern and enable company-wide adoption of emerging AI technologies We are seeking a pragmatic, highly technical individual to lead the engineering efforts within our Agentic Factory. Sitting directly alongside our AI Delivery Manager and AI Product Owner, you will bridge the gap between business requirements and technical execution. Together with the AI & Data Architect, you will provide architectural oversight, defining engineering best practices, and mentoring a talented team of AI engineers & Data Scientists, while remaining hands‑on enough to solve complex engineering bottlenecks; you will support Use Case Design and feasibility assessments, ensuring opportunities explored are achievable and scalable. You will support the Head of Engineering as the execution arm for AI responsibilities, extending your focus beyond the AI team to support and enable other IT teams across the organisation. • Design Agentic Systems: Design and scale robust, secure, and production‑ready multi‑agent workflows, orchestrations, and advanced RAG architectures, in collaboration with Enterprise Architecture principles. Drive delivery by designing and building agentic solutions, spanning from piloting to full implementation, • Define Engineering Excellence: Establish strict coding standards, code review processes, testing frameworks, and evaluation metrics for generative AI applications. Support and strictly enforce the standards set by the Head of Engineering and Technical Architect, • Cloud & Platform Integration: Partner closely with our GCP and Data Engineering teams to build seamless LLMOps/MLOps CI/CD pipelines, ensuring scalable and cost‑effective model deployment via Vertex AI and containerized environments. Take ownership of building and maintaining robust LLMOps pipelines, • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise‑grade safety, security, and compliance, • AI Safety & Guardrails: Implement robust evaluation frameworks, latency monitoring, and automated guardrails to ensure enterprise‑grade safety, security, and compliance, • Internal AI Enablement & Prompt Lifecycle: Manage the engineering workflows, CI/CD pipelines, version control, and evaluation frameworks for internal developer‑facing AI assets, including prompt libraries and automated testing agents, • Grow the team: Act as a technical mentor to a team of intermediate and junior AI Engineers, fostering a culture of continuous learning, clean code, and agility, • Pragmatic Delivery: Collaborate with the AI Product Owner and Business Analysts to translate abstract business use cases into structured, achievable technical sprints, • Drive MVP to Production: Shift the team's focus from sandboxed proof‑of‑concepts (PoCs) to reliable, resilient applications deployed to production for global users, leading AI engineering for AI team solutions and actively supporting junior engineers through this transition, • Support the company's evolving AI strategy, providing an expert voice on Use Case identification, platform identification and tool selection, • Advise the AI portfolio Lead in scaling impact and AI capability across the company, beyond the Group AI Team, • Stay up to date on market trends, new opportunities, and the changing landscape of AI technologies Expert‑level experience building complex LLM‑powered systems and multi‑agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Deep practical understanding of machine learning algorithms, natural language processing (NLP) techniques, and the optimization of large language models for enterprise deployment. Strong proficiency in designing optimized ELT/ETL pipelines and managing data lake/data warehouse architectures. Hands‑on experience with Google Cloud Platform (GCP) services including Vertex AI, BigQuery, Cloud SQL, and Google Cloud Storage (GCS). Proven track record of architecting pipelines for model deployment, performance tracking, hyperparameter tuning, and containerized workflows using Docker and Kubernetes (GKE/Vertex AI Pipelines). Extensive experience leading technical delivery, defining engineering milestones, running code reviews, and successfully mentoring junior or intermediate engineering talent. Works with high autonomy under broad strategic guidance. Accountable for defining and meeting technical, architectural, and delivery goals, establishing milestones, and assigning tasks. Exerts major technical influence across the organization, partners, and peers. Partners with cross‑functional business and product leaders, making key architectural decisions that affect budgets, timelines, and scalability. Manages diverse, highly complex, and unpredictable technical challenges. Uses fundamental engineering principles to connect cutting‑edge AI research with practical enterprise software. Advises executives on AI trends, risks, and tools. Bridges the gap between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem‑solving. • Python: Advanced, production‑grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code, • SQL: Expert querying, database design, partitioning, and optimization strategies for large‑scale BigQuery environments, • Google Cloud Certified Cloud Engineer, • Google Cloud Certified Professional Data Engineer / Cloud AI Engineer A Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a highly quantitative field is desirable; however, a proven track record of architecting and shipping production‑grade commercial AI systems is highly valued and may substitute for specific academic credentials. IT HNC/HND courses will also be accepted. • Competitive salary and bonus scheme, • Hybrid working, • Rentokil Initial Reward Scheme, • 23 days holiday, plus 8 bank holidays, • Employee Assistance Programme, • Death in service benefit, • Healthcare, • Free parking At Rentokil Initial, our customers and colleagues represent diverse backgrounds and experiences. We take pride in being an equal opportunity employer, actively encouraging applications from individuals from all walks of life. Our belief is that everyone irrespective of age, gender, gender identity, gender expression, ethnicity, sexual orientation, disabilities, religion, or beliefs, has the potential to thrive and contribute. We embrace the differences that make each of our colleagues unique, fostering an inclusive environment where everyone can be their authentic selves and feel a sense of belonging. To ensure that your journey with us is accessible if you have any individual requirements we invite you to communicate any specific needs or preferences you may have during any stage of the recruitment process. Our team is available to support you; feel free to reach out to () if you need anything Be Yourself in Your Application! At Rentokil Initial, we value innovation, but we want to see the real you! While AI can help with structure and grammar, make sure your application shows your true passion and understanding of the role. A personal touch will help you stand out. #J-18808-Ljbffr

Collaborate with senior developers and quantitative analysts to deliver reliable, high‑performance software solutions;. NET Developer – London – Up to £70,000 Starting Base + Exceptional Bonuses/Benefits. NET Developer to join their high‑performing engineering team.

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Seeking a graduate/junior developer with basic knowledge of Python, JavaScript, or PHP to join a growing social messaging platform expanding into UK and European markets.

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This is a traineeship for an AI Engineer role with no experience required.The online, self-paced course covers AI fundamentals, Python, machine learning, and data ethics, leading to a job guarantee and a starting salary of £28,000-£45,000.

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Position Title: Full Stack Senior Software Engineer.Sunday Times Tech 100 | Top 10 UK EdTech Company.BibliU is an award-winning education company that provides Day 1 access to affordable course materials, making learning more equitable and effective, in addition to providing campus store management.

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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.Our achievements include being recognised as Fintech of

Collabora is looking for a passionate and enthusiastic open-source software developer, with good knowledge of at least one of OpenGL or Vulkan, to join our ever growing geographically-distributed Graphics domain team.

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This opportunity is only for candidates currently residing in the specified country.Your location may affect eligibility and rates.We believe in using the power of collective intelligence to ethically shape the future of AI.The Mindrift platform connects specialists with AI projects from major tech

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We are looking for a passionate and enthusiastic open-source software developer, with contributions to the Mesa 3D Graphics Library, to join our ever growing geographically-distributed Graphics domain team.