Senior Lead AI Engineer

About the role

Oliver Wyman is seeking a senior technology leader to design and deliver secure, reliable AI solutions that integrate with enterprise business processes and technology estates. This applied engineering role focuses on production AI systems rather than research.

Key responsibilities

• Lead AI solution delivery from problem framing through production release and continuous improvement.
• Design pragmatic enterprise architectures linking AI capabilities with existing applications, APIs, data platforms, identity, security and operational controls.
• Develop critical components, set coding and testing standards, and guide engineering trade‑offs.
• Build production AI systems using agentic harnesses, retrieval‑augmented generation, function calling, structured outputs and multi‑agent workflows.
• Engineer inference architectures, model routing, caching, vector databases, evaluation pipelines, observability and cost optimisation.
• Define evaluation criteria, test sets and feedback loops for accuracy, reliability, safety, latency, cost and business impact.
• Embed responsible AI delivery with security, privacy, risk and legal guardrails.
• Collaborate with product owners, architects, data specialists and delivery teams to create roadmaps.
• Mentor engineers, contribute reusable patterns and promote AI engineering best practices.

Required profile

• 10‑12 years of experience in software engineering, solution architecture or platform engineering.
• Proven record of delivering production enterprise applications in complex, regulated or security‑focused environments.
• Recent hands‑on experience building AI‑enabled solutions such as agentic applications, RAG or intelligent workflow automation.
• Strong fundamentals in API design, distributed systems, automated testing, CI/CD, observability and secure development.
• Ability to lead multidisciplinary teams, mentor engineers and influence architecture without formal authority.

Required skills

• Python
• Java.NET or TypeScript/Node.js (at least one enterprise stack)
• Major cloud platform (AWS, Azure or Google Cloud)
• Kubernetes and container orchestration
• SQL and enterprise data integration
• Model evaluation, prompt design, responsible AI controls