Production AI Engineer: Multi-Agent & RAG Systems

Intelix.AI; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

Intelix.AI in London or Manchester offers a hybrid role to build production-grade AI products in a major regulated financial-services environment. The role requires hands-on AI/ML engineers with enterprise delivery experience beyond notebooks and prototypes.

You will design and build production AI, multi-agent systems, RAG pipelines, and tool-layer agents, while integrating with data platforms, implementing guardrails, CI/CD, and collaborating with Risk and Product teams.

Qualifications

• Production AI/ML, LLM, RAG or Agentic AI delivery experience.
• Strong Python and software engineering capability.
• Experience with APIs, microservices and system integration.

Responsibilities

• Design and build production AI, Generative AI and Agentic AI applications.
• Build multi-agent systems with defined roles, handoffs and shared state.
• Develop RAG pipelines, agent workflows and enterprise knowledge integrations.
• Build the tool layer agents with schema validation, retries, timeouts and audit trails.
• Build APIs and services using Python and modern backend frameworks.
• Integrate AI capabilities with internal systems, data platforms and business workflows.
• Implement evaluation, observability, guardrails and human-in-the-loop controls.
• Instrument agent behaviour, covering decision paths, tool-selection accuracy, loop containment and cost per request.
• Support deployment through CI/CD, cloud platforms and containerised environments.
• Work closely with Product Managers, Technical BAs, Architects, Data and Risk teams.
• Contribute to testing, operational readiness and production support.

Skills

Python

APIs

Microservices

Cloud platforms

Production AI/ML

LangChain

Tools

LangGraph

LangChain

Semantic Kernel

AutoGen

CrewAI

Job description

Intelix.AI in London or Manchester offers a hybrid role to build production-grade AI products in a major regulated financial-services environment. The role requires hands-on AI/ML engineers with enterprise delivery experience beyond notebooks and prototypes.

You will design and build production AI, multi-agent systems, RAG pipelines, and tool-layer agents, while integrating with data platforms, implementing guardrails, CI/CD, and collaborating with Risk and Product teams.