Senior AI Engineer

Lynx Recruitment Ltd

London, UK

4 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

2 years minimum

Compensation

£60,000.0 - £80,000.0

Working hours

Regular working hours

Job source

www.reed.co.uk

Tech stack

Artificial Intelligence Amazon Web Services Cloud Computing Continuous Integration Python (Programming Language) Machine Learning Software Deployment Large Language Models Multi-Agent Systems Prompt Engineering Virtual Agents

Job description

Design and deliver production GenAI and multi-agent systems
Build agentic workflows, RAG solutions, tool use and multi-step orchestration
Define evaluation strategies and implement AI observability
Design secure AWS deployment architectures
Build CI/CD pipelines and production-ready AI applications
Lead technical discussions with clients and senior stakeholders
Mentor engineers and provide technical leadership
Establish best practices around prompt design, guardrails and responsible AI

Requirements

3+ years of software or machine learning engineering experience
2+ years building and deploying GenAI/LLM applications in production
Strong Python development skills
Hands-on experience with LangGraph, LangChain, LlamaIndex, CrewAI or similar
Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker
Strong understanding of RAG, agentic AI and multi-agent architectures
Experience with CI/CD, cloud infrastructure and application deployment
Comfortable working directly with clients and senior stakeholders
Experience leading technical workstreams or small engineering teams
2:1 or above in an IT/Tech/Business related degree

About the company

Lynx Recruitment is working with a specialist technology and AI consultancy that is looking for a Senior AI Engineer to lead the design and delivery of production-grade Generative AI and agentic systems.

This is a hands-on technical role where you’ll take ownership from architecture and prototyping through to deployment, monitoring and continuous evaluation.