AI Engineer

Lynx Recruitment is partnering with a specialist data and AI consultancy to recruit an experiencedAI 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 operatingproduction-grade GenAI and agentic systems on AWS, supporting organisations across multiple industries.

As anAI 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 modernLLMs, 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.

• Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models)
• Build and deployRAG systems using vector databases and semantic search
• Developagentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar
• Create effectiveprompt engineering strategies with appropriate guardrails for production systems
• Implementmonitoring, evaluation and continuous improvement frameworks for GenAI applications
• Build and maintainCI/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

• 1+ year hands-on experience deploying GenAI / LLM applications into production
• Experience withAWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS
• StrongPython development skills with modern AI/ML libraries
• Practical experience using at least oneLLM API
• Solid understanding ofprompt engineering, RAG architectures and vector databases
• Experience withLangChain, LangGraph, LlamaIndex or similar frameworks
• Familiarity withGit and CI/CD workflows
• Bachelor’s degree in Computer Science, Engineering or a related discipline (2.1 or above)

• Hands-on experience buildingagentic AI systems with planning, tool use and multi-step reasoning
• Experiencefine-tuning or adapting LLMs for domain-specific use cases
• Familiarity withLLM evaluation frameworks (e.g. RAGAS, LangSmith)
• Knowledge ofLLM security, hallucination mitigation and responsible AI practices
• Master’s degree in AI, Machine Learning, Data Science or a related field