Production-Grade Generative AI Engineer (LLMs, Agents, RAG)

Lorien; Greater London; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Lorien in London is seeking AI Engineers and Applied AI specialists to join our growing AI function. You will build production-grade LLM and Generative AI applications, develop AI agents and agentic workflows, and design RAG and advanced retrieval solutions.

You will deploy AI applications across cloud environments, implement robust evaluation, monitoring and guardrails, and work with product, engineering and business teams to solve complex problems.

Qualifications

• Hands-on commercial experience with Python.
• Experience with agentic AI / AI agents.
• Experience with RAG techniques and retrieval augmented generation.
• Familiarity with LangChain, LangGraph, LlamaIndex or similar.
• Knowledge of MCP / FastMCP.
• Experience with OpenAI, Claude, Gemini or open-source LLMs.
• Experience with cloud providers (AWS Bedrock, Azure OpenAI, Vertex AI).
• Experience with FastAPI.
• Experience with LLM evaluation and observability.

Responsibilities

• Build production-grade LLM and Generative AI applications.
• Develop AI agents and agentic workflows.
• Design RAG and advanced retrieval solutions.
• Build single and multi-agent architectures.
• Integrate LLMs with enterprise tools, APIs and data.
• Develop robust AI evaluation, monitoring and guardrails.
• Deploy AI applications across cloud environments.
• Collaborate with product, engineering and business teams to solve complex problems.

Skills

Python

Agentic AI

RAG

FastAPI

LLM evaluation

Tools

LangChain

LangGraph

LlamaIndex

MCP

FastMCP

OpenAI

Claude

Gemini

AWS Bedrock

Azure OpenAI

Vertex AI

Job description

Lorien in London is seeking AI Engineers and Applied AI specialists to join our growing AI function. You will build production-grade LLM and Generative AI applications, develop AI agents and agentic workflows, and design RAG and advanced retrieval solutions.

You will deploy AI applications across cloud environments, implement robust evaluation, monitoring and guardrails, and work with product, engineering and business teams to solve complex problems.