Senior/Lead AI Engineer

The Role

Joining a leading global technology consultancy within a growing Data & AI practice, working on cutting-edge AI engineering initiatives across a range of industries.

You'll design, develop and deploy production-grade Generative AI and Agentic AI solutions, combining strong Data Science / Machine Learning foundations with modern software engineering practices.

This is a hands-on technical role with opportunities to influence solution architecture, develop scalable AI applications and work closely with clients on complex AI transformation projects.

Key Responsibilities

• Design, build and deploy Generative AI and Agentic AI solutions from initial prototype through to production
• Develop multi-agent systems and orchestration workflows using frameworks such as LangGraph, CrewAI, AutoGen or Semantic Kernel
• Design and implement RAG pipelines, incorporating embeddings, vector databases, hybrid search and retrieval optimisation
• Build scalable Python applications, APIs and microservices to integrate AI capabilities with enterprise systems
• Develop and optimise LLM-powered applications, including prompt engineering, tool calling, evaluation and performance monitoring
• Implement AI orchestration patterns, including multi-step planning, agent collaboration, fallback handling and workflow management
• Deploy AI solutions across cloud environments, ensuring scalability, reliability and security
• Contribute to technical architecture decisions, engineering best practices and the ongoing development of AI capabilities

Key Requirements

• Strong background in Data Science, Machine Learning or AI Engineering, with proven experience deploying models or AI applications into production
• Excellent Python engineering skills, including experience developing APIs, microservices and production-ready applications
• Hands-on experience building and deploying Generative AI / LLM-based solutions in production environments
• Experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel or similar
• Strong understanding of RAG architectures, embeddings, vector databases and LLM evaluation techniques
• Experience working with cloud platforms, ideally Azure, although AWS experience is also considered
• Familiarity with containerisation, CI/CD and MLOps practices
• Understanding of AI orchestration, tool integration and emerging protocols such as MCP and A2A would be advantageous
• Strong academic background in Computer Science, Mathematics, Physics, Data Science or a related technical discipline (PhD advantageous)
• Strong communication and problem-solving skills, with the ability to engage with technical teams and client stakeholders

No sponsorship available.: Get in touch for more details – ncarolan@mcgregor-boyall.com