AI Engineer

Experis; Greater London; On-site; GBP 111,000 - 119,000; Full time

Job summary

Experis seeks an AI Engineer to join a product squad and deliver GenAI/Agentic AI products. You will design and build production-grade GenAI solutions using LLMs, RAG, and agentic workflows, with a strong emphasis on Python engineering and secure, maintainable applications.

Role requires hands‑on experience with LangGraph and Azure AI services, plus a solid understanding of end-to-end AI pipelines, tooling, and QA processes. Remote with monthly on-site support is offered.

Qualifications

• Hands-on experience building production-grade GenAI/LLM solutions with Python.
• Experience with RAG architectures and document ingestion.
• Knowledge of Azure AI services including OpenAI, Cosmos DB, and monitoring.
• Strong software engineering practices: testing, code reviews, maintainable design.
• Experience handling guardrails, grounding, and AI assurance.

Responsibilities

• Work with a Product squad to design, build and deliver GenAI/Agentic AI products.
• Develop production-grade GenAI/LLM solutions using LLMs, RAG and agentic workflow technologies.
• Ensure secure, reliable, and maintainable AI-enabled applications; write clean Python code.

Skills

Python

GenAI/LLM development

Agentic AI design

LLM workflow design

RAG architectures

APIs & backend

Software testing & maintainable design

Observability

Tools

LangGraph

Azure OpenAI

Azure AI Search

Cosmos DB

Redis

Key Vault

Job description

AI Engineer

Rate: £600 - £644

Clearance required: BPSS + SC

Nationality requirement: UK Passport Holder

Location: Remote (on-site once a month)

Job Description:

The AI Engineer role will be responsible for working within a Product squad to design, build and deliver GenAI and Agentic AI products. The individual must have hands‑on experience developing production‑grade GenAI/Agentic AI solutions using LLMs, RAG and agentic workflow technologies. The role requires strong Python software engineering skills alongside practical experience designing reliable, secure and maintainable AI-enabled applications.

• Strong Python software engineering experience
• Hands‑on experience developing GenAI / LLM applications
• Hands‑on experience designing and implementing Agentic AI workflows
• Experience with LangGraph
• Strong understanding of LLM workflow design, including state, routing, tools, structured outputs and human‑in‑the‑loop patterns
• Practical experience designing and implementing RAG architectures
• Experience with document ingestion, chunking, embeddings and vector/semantic search
• Experience with prompt engineering and structured LLM outputs
• Experience with AI/LLM evaluation, testing and quality assurance
• Understanding of guardrails, grounding, hallucination mitigation and AI assurance
• Experience building and integrating APIs and backend services
• Strong understanding of software engineering principles, automated testing, code review and maintainable application design
• Experience handling LLM and agent failure scenarios, retries, error handling and recovery
• Understanding of observability and tracing for GenAI/Agentic AI applications
• Azure AI & Cloud Services: Hands‑on experience building and deploying AI solutions on Azure, including Azure OpenAI, Azure AI Search, Azure AI Foundry, Cosmos DB, Redis, Azure Monitor/Application Insights, Managed Identity and Key Vault.