Lead Agentic AI Engineer

We are seeking a highly skilled and innovative Lead Agentic AI Engineer to join our team and drive the design, development, and deployment of production‑grade generative AI and agentic solutions using Microsoft technologies. This role is ideal for a technically strong engineer who has hands‑on experience building AI solutions, orchestrating agentic workflows, implementing evaluation frameworks, and taking solutions into secure, scalable, and cost‑optimised production environments using platforms such as Azure AI Foundry, Microsoft Agent Framework, and Copilot Studio.

• Take ownership of technical solution design and architecture decisions, bringing clarity from ambiguous client requirements
• Act as the technical lead on projects, guiding implementation approach, engineering standards, and best practices
• Design, develop, and deploy Agentic AI and GenAI solutions in enterprise environments
• Lead end‑to‑end solution delivery, from discovery and design through implementation, deployment, and handover
• Make clear technical design decisions that support scalability, reliability, security, and maintainability
• Lead and mentor junior team members, helping them deliver high‑quality outcomes and grow their technical capability
• Collaborate effectively with cross‑functional teams in agile environments
• Manage technical stakeholders and client conversations, translating business needs into practical AI solution designs
• Support or lead pre‑sales activities, including solution shaping, technical estimations, demos, proposals, and client discussions
• Lead implementation during delivery, ensuring the proposed solution is built to the agreed architecture and quality standards

• Hands‑on experience with LLMs such as OpenAI GPT, Claude, Gemini or Mistral
• Experience designing and building agentic AI solutions, including tool use, workflow orchestration, routing, memory, and multi‑agent patterns
• Expertise in prompt engineering, structured outputs, and reliability patterns to optimise model performance
• Ability to implement evaluation frameworks for quality, grounding, task success, safety, latency, and cost
• Experience deploying AI solutions into production with focus on cost optimisation, scalability, observability, security, and governance
• Experienced in using Microsoft GenAI ecosystem, including M365, Copilot Studio, Azure AI Foundry, and Microsoft Agent Framework
• Proficient in Python and production‑quality code practices
• Strong understanding of software engineering principles, architecture patterns, and delivery best practices
• Experience with API development using frameworks such as FastAPI, Flask, or Django
• Knowledge of Docker, containerised deployments, CI/CD, and cloud‑native delivery patterns

• Experience building, deploying, and evaluating multi‑agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations
• Knowledge of agent communication protocols and interoperability patterns, such as MCP and A2A
• Ability to balance innovation with practical delivery considerations, including risk, cost, security, and production readiness
• Confidence contributing to pre‑sales while also being able to lead implementation during delivery
• Curiosity and motivation to stay current with the latest advancements in GenAI, agentic AI, and AI engineering frameworks

• Bachelor’s degree in Computer Science, Data Science, or a related field
• Microsoft certified i.e. Azure AI Apps and Agents Developer Associate or Agentic AI Business Solutions Architect