AI Full-Stack Engineer (Agentic AI)

The Opportunity

We're looking for an experienced AI Full-Stack Engineer to join a high-profile programme, building production-grade Agentic AI solutions for a global financial services organisation.

This role is ideal for a strong Python engineer with full-stack development experience who is passionate about applying the latest AI technologies to solve complex business problems.

You'll design, build and deploy intelligent multi-agent systems, integrating Large Language Models (LLMs) into secure, scalable production environments.

Working as part of a collaborative engineering team, you'll help deliver reliable AI applications with a strong focus on performance, security, testing and observability.

Key Responsibilities

• Design, develop and deploy production-grade Agentic AI applications.
• Build multi-agent systems and stateful workflows using frameworks such as Google ADK, LangChain and LangGraph.
• Develop secure Python APIs and integrate external tools and services into AI workflows.
• Engineer effective prompts, manage conversational state and optimise context handling for LLM applications.
• Design structured outputs using JSON schemas and Pydantic models to ensure reliable responses.
• Implement guardrails, fallback mechanisms and safety controls to improve AI reliability and reduce hallucinations.
• Develop observability and monitoring solutions, including tracing, logging and evaluation frameworks for AI systems.
• Build scalable backend services and contribute to full-stack application development.
• Work closely with architects, product owners and engineering teams to deliver high-quality solutions.
• Write clean, well-tested code and contribute to CI/CD pipelines and automated deployments.

Skills & Experience

We're looking for candidates with:

Strong commercial experience developing backend applications using Python.

Experience building APIs, microservices and distributed systems.

Hands-on experience with Large Language Models, including OpenAI, Gemini or Claude APIs.

Experience using AI orchestration frameworks such as LangChain, LangGraph or similar.

Strong understanding of Google Cloud Platform (GCP) services and architecture.

Experience building and deploying cloud-native applications.

Knowledge of containers, Docker, Kubernetes and CI/CD pipelines.

Experience writing unit, integration and automated tests.

Excellent problem-solving skills and a systems-thinking approach to software design.

Essential Requirements

• Google Professional Cloud Architect Certification (essential).
• Strong Python engineering background.
• Experience developing production-grade AI or LLM-enabled applications.
• Ability to work onsite in London five days per week.

Desirable Experience

• Experience with Agentic AI architectures.
• Knowledge of asynchronous workflows and event-driven systems.
• Exposure to AI evaluation frameworks and prompt testing.
• Financial services experience would be advantageous.