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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # senior ai solutions engineer - technical lead. - **Company:** Randstad UK - **Location:** Welwyn Garden City, United Kingdom - **Experience:** Expert - **Salary:** £182,000 - £221,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Business Systems, Cloud Database, Cluster Analysis, Cyber Security, Continuous Integration, Data Governance, Data Integration, Data Security, Github, R (Programming Language), Python (Programming Language), Machine Learning, OpenAI, Cloud Services, Search Technologies, Software Engineering, System Testing, Systems Integration, AI Infrastructure, Data Logging, Sql Optimization, Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, Generative AI, Agentic-AI, Git, Fastapi, Pandas, Build Management, Pytest, Containerization, AI Platforms, Information Technology, CrewAI, AutoGen, Claude, Evaluation of Large Language Models, Restful APIs, Software Version Control, GXP, Docker - **Published:** November 10, 2026 - **Apply:** https://www.randstad.co.uk/jobs/senior-ai-solutions-engineer-technical-lead_welwyn-garden-city_47731731/ ## About the Role * Experience: At least 4 years in software, data or machine-learning engineering, including 2+ years building LLM-based applications or agents that are used in production. * Project Management: Led technical project execution for complex AI/ML engagements, translating business requirements into scalable cloud architectures and managing timelines, risks, and deployment roadmaps across multiple enterprise accounts . * Python: Expert, production-quality Python (for example FastAPI, Pydantic, asyncio, pandas, pytest). * R and R Shiny: Solid R and experience building and deploying Shiny applications. * LLM and agent engineering: Hands-on experience with LLM APIs (Anthropic Claude, OpenAI or similar), tool calling and connector patterns, RAG and vector search, agent frameworks (for example LangGraph, CrewAI or AutoGen) and LLM evaluation. * Data and integration: Advanced SQL and working proficiency with Snowflake; integrating enterprise systems through REST APIs. * Engineering practices: Git, CI/CD, containerisation (Docker), cloud services (AWS) and observability (logging, tracing, metrics). * Regulated environments: Understanding of GxP, computer system validation, data privacy and reproducibility for AI in a regulated industry. * Communication: Explains complex technical choices in plain language to non-technical stakeholders and turns loosely described needs into clear technical scope. * You are a strategic, hands-on engineer who thrives where software engineering, AI orchestration and real business impact meet. You value reliability and reproducibility, and you explain technical choices clearly to colleagues across BSO. * Education: Bachelor's or advanced degree in Computer Science, Engineering, Data Science or a related field. Preferred Qualifications * Master's or PhD in Computer Science, AI or a related quantitative field. * In-platform AI services in cloud data warehouses. * End-to-end security of agentic workflows (permissions, data access and protection against prompt injection). * Experience with validated quality management or other regulated enterprise systems. * Classical machine learning (for example scikit-learn) for trend analysis, clustering and forecasting. * Experience in pharmaceutical R&D or another highly regulated industry. * A GitHub profile or portfolio showing relevant work is an advantage. ## Description As a Senior AI Solutions Engineer you are the Technical Lead lead for my client's AI solutions, reporting to the Business Digital, Data & AI Infrastructure Lead. You will design and build the AI agents, assistants and agentified dashboards/cockpits that let BSO move from manual assembly to AI-enabled workflows, and set the patterns, standards and shared components that others reuse. You will be part of Business Digital, Data & AI Infrastructure sub-function, which designs, builds and runs the data, digital and AI capabilities used across my client You will work closely with business teams, IT & Architecture, Data Governance, Information Security and Quality & Compliance. You will turn business needs into production-grade solutions that are secure, traceable and, where required, GxP-compliant - taking my client step by step from AI assistants to supervised and orchestrated agents., * AI solution architecture: Own the technical design AI solutions - agents, assistants, AI interfaces and automations. Favour adopting and configuring existing capabilities before building, and design for reuse across teams. * Agentic AI and LLM engineering: Build agents and assistants on enterprise large language models: tool calling, connectors to business systems, retrieval-augmented generation (RAG) over procedural and quality documents, and prompt and context engineering, including multi-agent workflows where specialised agents plan, execute and check the work. * AI interfaces over business data: Build natural-language interfaces and agentified dashboards over clien'ts portfolio, resourcing and performance data, so leaders can ask questions, see trends and act on alerts. * Shared foundation: Build and govern a shared library of reusable AI skills and components, so a capability built once is used across the client * GxP and trust by design: Partner with Quality & Compliance on the validation path for regulated AI use cases: human-in-the-loop decisions, audit trails, reproducibility, guardrails and computer system validation evidence. * Evaluation and operations: Define test sets and accuracy measures, monitor quality, cost and usage in production, and maintain documentation and runbooks. * Technical leadership: Set coding and review standards, CI/CD and version-control practices; mentor engineers and support the business colleagues who adopt and champion AI in their teams. * Stakeholder partnership: Translate business needs into technical scope, and work with IT & Architecture, Information Security, Data Governance and PDD AI experts on platform, access and privacy decisions.