Details:
- Salary: £410 - 430 - Day
- Job Type: Contract
- Job Status: Full-Time
- Salary Per: Day
- Location: London
- Date: 1 day ago
Description:
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
Build and maintain stateful workflows, orchestration layers, and agent decision-making processes
Develop secure, scalable Python APIs and backend services that integrate with AI agents and enterprise systems
Implement effective prompt engineering strategies, context management, memory handling, and system instructions
Create reliable, structured outputs using JSON schemas and Pydantic validation
Design and implement guardrails, fallback mechanisms, circuit breakers, and hallucination mitigation strategies
Build observability frameworks, tracing tools, and evaluation-as-code capabilities to monitor agent behaviour and performance
Collaborate with engineering and architecture teams to deploy AI solutions within cloud-native environments
Ensure best practices across testing, security, scalability, and maintainability
Required Skills & Experience
Essential
Strong commercial experience in Python development, backend engineering, and distributed systems
Experience building APIs, microservices, and scalable production applications
Hands-on experience with LLM platforms including OpenAI, Gemini, Claude, or similar
Proven experience with LangChain, LangGraph, Google ADK, or related AI orchestration frameworks
Strong understanding of agentic architectures, workflow orchestration, and AI application design
Experience working with Google Cloud Platform (GCP)
Google Professional Cloud Architect Certification (mandatory)
Knowledge of containerisation technologies and cloud deployments (Docker, Kubernetes, CI/CD pipelines)
Strong testing mindset, including unit, integration, and automated testing approaches for AI-driven systems
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
Exposure to observability tools, tracing frameworks, and AI evaluation platforms
Experience working within large-scale enterprise environments, particularly financial services