AI Full Stack Engineer

AI / ML Engineer (Agentic AI Full-Stack Engineering) Location: London (5 Days Onsite) Client: J.P. Morgan Chase (JPMC) Contract Duration: 14-16 Weeks Pay: £410 - £430 per day (Inside IR35 / Umbrella( Contract Type:

Fixed-Term / Contract Opportunity The Opportunity We're partnering with JPMC to hire an experienced AI / ML Engineer with a strong full-stack Python background and proven expertise in building production-grade Agentic AI applications.

This is an exciting opportunity to work on cutting-edge AI initiatives, designing and delivering intelligent agent workflows that are scalable, reliable, secure, and enterprise-ready.

You'll be responsible for building sophisticated multi-agent systems, integrating LLM capabilities into business processes, and ensuring robust governance, observability, and performance across the AI stack.

Key Responsibilities Design and develop multi-agent AI systems using frameworks such as Google ADK, LangChain, and LangGraph<br />Build and maintain stateful workflows, orchestration layers, and agent decision-making processes<br />Develop secure, scalable Python APIs and backend services that integrate with AI agents and enterprise systems<br />Implement effective prompt engineering strategies, context management, memory handling, and system instructions<br />Create reliable, structured outputs using JSON schemas and Pydantic validation<br />Design and implement guardrails, fallback mechanisms, circuit breakers, and hallucination mitigation strategies<br />Build observability frameworks, tracing tools, and evaluation-as-code capabilities to monitor agent behaviour and performance<br />Collaborate with engineering and architecture teams to deploy AI solutions within cloud-native environments<br />Ensure best practices across testing, security, scalability, and maintainability Required Skills &amp; Experience Essential Strong commercial experience in Python development, backend engineering, and distributed systems<br />Experience building APIs, microservices, and scalable production applications<br />Hands-on experience with LLM platforms including OpenAI, Gemini, Claude, or similar<br />Proven experience with LangChain, LangGraph, Google ADK, or related AI orchestration frameworks<br />Strong understanding of agentic architectures, workflow orchestration, and AI application design<br />Experience working with Google Cloud Platform (GCP)<br />Google Professional Cloud Architect Certification (mandatory)<br />Knowledge of containerisation technologies and cloud deployments (Docker, Kubernetes, CI/CD pipelines)<br />Strong testing mindset, including unit, integration, and automated testing approaches for AI-driven systems<br />Ability to design resilient systems that manage asynchronous events, state transitions, and complex decision paths Desirable Experience implementing AI governance frameworks and responsible AI practices<br />Exposure to observability tools, tracing frameworks, and AI evaluation platforms<br />Experience working within large-scale enterprise environments, particularly financial services