AI Engineer

Lynx Recruitment is partnering with a specialist data and AI consultancy to recruit an experienced AI Engineer to work on cutting-edge Generative AI and agentic AI solutions.

Our client delivers data platforms, advanced analytics and AI/Machine Learning solutions that drive tangible business outcomes. The focus is on designing, deploying and operating production-grade GenAI and agentic systems on AWS, supporting organisations across multiple industries. Role Overview As an AI Engineer, you will design, develop and deploy production-ready Generative AI solutions for enterprise clients. You will be involved across the full lifecycle of GenAI products—from proof of concept through to scalable production deployment and monitoring.

Working with modern LLMs, RAG architectures and agentic frameworks, you’ll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS. Key Responsibilities

Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models)

Build and deploy RAG systems using vector databases and semantic search

Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar

Create effective prompt engineering strategies with appropriate guardrails for production systems

Implement monitoring, evaluation and continuous improvement frameworks for GenAI applications

Build and maintain CI/CD pipelines for testing, deployment and version control

Work directly with client stakeholders to gather requirements, demonstrate solutions and iterate delivery

Document architecture designs, decisions and best practices

Required Skills & Experience

1+ year hands-on experience deploying GenAI / LLM applications into production

Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS

Strong Python development skills with modern AI/ML libraries

Practical experience using at least one LLM API

Solid understanding of prompt engineering, RAG architectures and vector databases

Experience with LangChain, LangGraph, LlamaIndex or similar frameworks

Familiarity with Git and CI/CD workflows

Bachelor’s degree in Computer Science, Engineering or a related discipline (2.1 or above)

Highly Desirable

Hands-on experience building agentic AI systems with planning, tool use and multi-step reasoning

Experience fine-tuning or adapting LLMs for domain-specific use cases

Familiarity with LLM evaluation frameworks (e.g. RAGAS, LangSmith)

Knowledge of LLM security, hallucination mitigation and responsible AI practices

Master’s degree in AI, Machine Learning, Data Science or a related field