AI Engineer (Agentic SDLC Expert- VP) - London
Role overview
FDM is a global business and technology consultancy seeking an AI Engineer- Agentic SDLC Expert (VP) to work for our client within the Financial Services sector. This is initially an 8-month fixed-term contract with very good prospects to extend and will be a hybrid role based in London.
Our client is seeking an experienced AI Engineer- Agentic SDLC Expert to lead the transformation of software engineering through the adoption of Generative AI, Large Language Models (LLMs), AI Agents and AI-native software delivery practices. You will be responsible for designing, building and operationalising enterprise-scale Agentic SDLC platforms that automate and accelerate activities across the software development lifecycle, from requirements analysis and architecture design through to testing, deployment and continuous improvement. This is a strategic opportunity to shape AI-assisted software development at scale, driving engineering productivity, software quality and delivery speed across a complex enterprise environment.
Responsibilities
- check_circle Design and implement Agentic SDLC platforms and AI-native engineering workflows that automate key stages of the software development lifecycle.
- check_circle Build and orchestrate intelligent multi-agent systems, AI workflows, prompt chains, knowledge retrieval solutions and Model Context Protocol (MCP) integrations.
- check_circle Develop AI-powered engineering accelerators that support requirements analysis, solution design, code generation, test automation, documentation and deployment readiness validation.
- check_circle Integrate AI capabilities across enterprise engineering platforms including GitHub Enterprise, GitHub Copilot, GitHub Actions, CI/CD tooling and organisational knowledge repositories.
- check_circle Establish AI engineering governance frameworks, including human-in-the-loop processes, model governance controls, auditability standards and AI output validation mechanisms.
About the company
- check_circle Minimum 10 years' experience in software engineering, platform engineering or enterprise technology environments, with significant exposure to AI-driven development practices.
- check_circle Strong experience with Large Language Models (LLMs), Generative AI, AI Agent frameworks, agent orchestration, prompt engineering and AI workflow automation.
- check_circle Hands-on experience designing or implementing AI-driven development workflows, autonomous engineering agents, SDLC automation platforms and developer productivity solutions.
- check_circle Strong technical background in Java development, Spring Boot, API design, enterprise architecture, distributed systems, build and release engineering and software troubleshooting.
- check_circle Experience with GitHub Enterprise, GitHub Copilot, GitHub Actions, Jenkins, Maven, OpenShift, Kubernetes, Docker and public cloud platforms such as GCP.
- check_circle Strong understanding of Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), tool calling, function calling, multi-agent systems, grounded AI systems and AI evaluation frameworks.
- check_circle Experience with LangGraph, OpenAI Agents SDK and Agent Evaluation Frameworks.
- check_circle Knowledge of knowledge graphs, ontologies and graph-based knowledge systems.
- check_circle Experience with AI observability, AI governance platforms and prompt lifecycle management.
- check_circle Exposure to Internal Developer Platforms (IDPs), platform engineering and application modernisation initiatives.
- check_circle Strong understanding of modern software architecture and engineering transformation programmes