5 jobs found

Permanent - AI Full Stack Product Engineer (Agentic AI) Location: London (Hybrid - 3 days per week) Permanent Build AI Products. Not Just Software. We're looking for a hands-on AI Full Stack Product Engineer to help build the next generation of AI-powered products for a fast-growing technology business. Working directly with an innovative CTO, you'll develop intelligent applications using Agentic AI , LLMs and frameworks such as Loop Harness and LangGraph , helping shape how AI is Embedded into real-world products. This is a role for someone who enjoys experimenting, moving quickly and solving complex problems in a collaborative scale-up environment. What You'll Be Doing Build AI-powered products using modern full-stack technologies. Develop agentic workflows and autonomous AI capabilities. Build and integrate APIs, Back End services and cloud-native applications. Work with LLMs including Anthropic Claude and other leading AI platforms. Prototype new ideas and rapidly iterate with Product and Engineering teams. Contribute across Front End, Back End, cloud infrastructure and AI engineering. Help define engineering standards and best practices for AI development. Skills We're Looking For Strong commercial experience with TypeScript , Next.js and React . Backend development using Python and modern APIs. Experience building production applications using LLMs or AI services. Knowledge of LangGraph , Loop Harness , MCP or similar agent frameworks. AWS, Docker, Kubernetes and CI/CD experience. Comfortable working across the full technology stack. Experience within a fast-paced scale-up or product-led business. The Person We're looking for someone who is: Passionate about AI and emerging technologies. Curious, energetic and keen to experiment. Comfortable working in ambiguity and trying new approaches. A strong communicator who enjoys collaborating across Product and Engineering. Happy wearing multiple hats and helping a growing business scale. This is an opportunity to work on cutting-edge AI products where you'll have genuine influence over technical direction, work directly with the CTO and help shape the future of an AI-first business.

About Scrumconnect Consulting 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. Overview 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. Key Responsibilities 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. Required Skills & Experience 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 Desirable Experience - 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. Location and Working Pattern 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. How We Work 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. How to Apply Please submit your CV. Shortlisted candidates will be invited to interview. This role requires BPSS (Baseline Personnel Security Standard) clearance - please flag in your application if you already hold clearance.

AI Engineer (.Net/AI) Location: Chester Hybrid Working Permanent Full-time Salary: £50,000 £60,000 We're working with a leading UK organisation that is continuing to invest in its internal AI capability and is looking for an AI Software Engineer to join its dedicated AI squad. This role sits at the intersection of software engineering and applied AI. Rather than relying heavily on off-the-shelf products, the organisation is building its own enterprise-grade applications and AI solutions, designed around real business challenges and used across a large-scale operational environment. The Role As an AI Software Engineer, you'll use strong software engineering principles to design, build and deploy production-ready applications that incorporate AI, automation and machine learning capabilities. You'll be involved across the full software development lifecycle, from technical design and development through to testing, deployment and ongoing improvement. Responsibilities will include: Designing and developing scalable, maintainable software solutions using .NET/C# and Microsoft Azure. Building AI capabilities into enterprise applications and existing business processes. Developing solutions using Microsoft AI Foundry, Agent Framework and Azure AI services. Designing APIs, services and integrations to connect AI capabilities with wider enterprise systems. Building agentic AI applications, including multi-agent workflows and orchestration. Developing RAG solutions using vector search, enterprise data and retrieval techniques. Writing clean, maintainable and well-tested production code. Working with CI/CD pipelines, source control, automated testing and DevOps practices. Ensuring applications are secure, scalable, resilient and observable. Contributing to architecture, technical design and engineering standards. Working with stakeholders to understand business problems and translate them into effective software solutions. What We're Looking For Strong commercial software engineering experience, ideally within the Microsoft technology stack. Good development experience with C#/.NET and modern software engineering practices. Experience designing, building and deploying production applications within Microsoft Azure. Exposure to building AI-enabled applications using technologies such as Azure AI, Microsoft AI Foundry, Azure OpenAI, Semantic Kernel, Agent Framework or similar. Understanding of RAG, LLMs, vector search and agentic AI concepts. Experience integrating applications with APIs, cloud services and enterprise systems. Strong understanding of DevOps, CI/CD, source control and automated testing. Experience building secure, scalable and maintainable production software. An interest in emerging AI technologies and how they can be applied to solve real business problems. You don't need to come from a traditional Data Science background. We're particularly interested in Software Engineers who have started building with AI and want AI engineering to become a bigger part of their career. This is an opportunity to join an established software engineering function with a dedicated AI capability, combining strong engineering practices with some of the latest developments across Microsoft AI. If you are interested in this opportunity and would like to hear more, please apply for the opportunity with an updated CV and contact information. (url removed)

About Scrumconnect Consulting 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. Overview We're looking for a Lead Technical Architect (AI) to act as the technical authority for a full-scale AI Operating Model and Responsible AI Governance Framework at a central government department. This is a large, high-visibility AI adoption and scale-up programme covering systems and services handling high-volume, sensitive public sector data. You'll work as part of a collaborative "Rainbow Team" alongside civil servants, with a mission that goes beyond delivery: build sustainable internal capability so the department can eventually operate and govern its own AI capability without long-term reliance on external suppliers. Key Responsibilities Architectural Leadership & Integration Design and implement enterprise-grade AI platforms - including semantic search, Retrieval-Augmented Generation (RAG), and broader generative AI/agentic capabilities - integrating cleanly with the department's complex Legacy and multi-cloud environments. Responsible AI Governance Embed end-to-end responsible AI controls across the full life cycle: alignment with the Algorithmic Transparency Recording Standard (ATRS), NCSC "Secure by Design" principles, and active mitigation of algorithmic bias. Ensure every system operates as a decision-support tool that enforces meaningful human control. Risk & Value Management Navigate trade-offs between value, risk, pace, and quality using HM Treasury Orange Book and Technology-Organisation-Environment (ToE) frameworks. Identify and resolve systemic risks via Joint Risk Registers. Zero-Dependency Handover & Capability Uplift Co-deliver within blended agile teams. Drive knowledge transfer using the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs-as-Code" practices so internal staff can independently operate and govern AI capability long after the engagement ends. Environmental Sustainability (Green AI) Design low-modality, energy-efficient AI architectures aligned with "Circularity Performance Requirements" (Buy Better, Use Better, Use Longer), supporting Net Zero 2030/2040 commitments. Required Skills & Experience Mapped to the Government Digital and Data (DDaT) framework: Technical Design Throughout the Life Cycle (Expert) : technical designs for high-risk, high-impact, high-complexity systems; leading others toward organisational objectives; refining standards from feedback. Architecture Communication (Expert): communicating complex or contentious architecture to technical and non-technical stakeholders at all levels; mediating difficult discussions; securing executive buy-in. Making Architectural Decisions (Practitioner): medium-to-high-risk design decisions spanning multiple domains; active contribution to architectural governance and assurance boards. Architect for the Whole Context (Practitioner): tracking emerging AI and technology trends; influencing colleagues across the organisation to solve or mitigate problems. Strategy Design (Practitioner): defining architectural principles, AI patterns, and strategic vision aligned to wider government objectives; building implementation roadmaps. Community Collaboration (Practitioner): proactive networking, resolving team-dynamics issues, using Agile health checks to strengthen the multidisciplinary delivery team. Alongside the DDaT competencies, given the scale of this programme, hands-on depth across the modern AI engineering stack is essential, not just RAG in isolation: Semantic search, vector/embedding infrastructure, and retrieval architecture design LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) LLM evaluation, guardrails, and red-teaming tooling (hallucination detection, safety/bias testing) LLMOps/MLOps: model versioning, deployment pipelines, monitoring, and rollback for AI services in production Fine-tuning and parameter-efficient adaptation techniques where appropriate to use case Data engineering for AI: ingestion, cleaning, and lineage across Legacy and multi-cloud sources Infrastructure-as-Code and CI/CD practices adapted for AI workloads, with strong observability Secure-by-design engineering appropriate to sensitive public-sector data (identity, access control, data protection) Desirable Experience AWS/Azure/GCP architecture certifications, AI related certifications most desirable. Experience contributing to GOV.UK Service Standard Alpha or beta assessments Prior delivery of AI or digital services within UK central government or wider public sector Familiarity with ATRS submissions, HM Treasury Orange Book, or equivalent public-sector risk/assurance frameworks Open-source contributions or active engagement in engineering/AI communities Experience designing for sustainability/Green IT commitments Location and Working Pattern Hybrid, based from Newcastle upon Tyne, with on-site attendance required for workshops, knowledge-transfer sessions, and onboarding. All production systems and data access must be performed solely from within the UK. How We Work 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.

Senior Full Stack Engineer (AI Systems) Remote (United Kingdom) | Permanent | Flexible compensation (DOE) + bonus + equity We're working with a well-funded AI-first technology business building systems that go beyond traditional chatbot experiences and execute real-world workflows autonomously. The team is building AI-native products designed to handle long-running tasks, maintain context over time, interact with external systems, and reliably help users achieve goals with minimal prompting. This is a highly product-focused engineering role where you'll help turn AI capabilities into dependable user experiences that work consistently in production. The Opportunity This role sits at the intersection of: AI systems Product engineering User experience Backend workflows You'll be responsible for building the product layer that connects AI systems to real user outcomes. Areas of responsibility include: Building end-to-end product features across Front End, Back End, and AI systems Designing agent workflows that handle planning, tool use, recovery, and multi-step execution Integrating LLMs, retrieval systems, memory, and external services into user-facing products Designing Real Time AI interactions, including streaming and partial responses Building resilient user experiences through fallback and recovery mechanisms Continuously improving AI workflow performance based on production usage and feedback Collaborating closely with ML, Back End, and product teams to ship features end-to-end What They're Looking For The team is particularly interested in engineers who have built AI-powered products used by real users. Examples of relevant experience include: LLM-powered applications Retrieval-Augmented Generation (RAG) Agentic workflows Multi-agent systems Tool calling and orchestration AI assistants Workflow automation Vector databases and semantic search AI evaluation and monitoring Real Time user interactions Technical Environment Next.js Python Node.js SQL/NoSQL OpenAI, Anthropic and open-source LLMs DevOps - Docker/ Kubernetes AWS, Azure or GCP Compensation Compensation is intentionally flexible and assessed based on experience, ownership, and production impact. The package includes: Competitive base salary Performance-based bonus Equity Fully remote working Private healthcare Pension contribution Dental/Vision/Life insurance Generous paid holiday allowance