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, data, 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 architecture, implementation, production release and continuous improvement.
• Design pragmatic enterprise architectures that connect AI capabilities with existing applications, APIs, data platforms, identity, security and operational controls.
• Develop and review critical components, establish coding and testing standards, and guide teams on quality, cost, speed and maintainability trade‑offs.
• Build production AI systems using agentic harnesses, retrieval‑augmented generation, function calling, structured outputs and multi‑agent workflows.
• Engineer AI platforms with inference architectures, model routing, caching, semantic retrieval, vector databases, evaluation pipelines, observability and cost optimisation.
• Define evaluation criteria, test sets and feedback loops to measure accuracy, reliability, safety, latency, cost and business impact.
• Embed responsible delivery by working with security, privacy, risk and legal partners to implement guardrails and auditability.
• Collaborate with product owners, architects, data specialists and delivery teams to translate priorities into roadmaps.
• Mentor engineers, contribute reusable patterns and help teams adopt effective AI engineering practices.

Required profile

• 10‑12 years of professional experience in software engineering, solution architecture or platform engineering.
• Proven record of designing and delivering production enterprise applications in complex, regulated or security‑focused environments.
• Hands‑on experience implementing AI‑enabled solutions such as agentic applications, RAG or intelligent workflow automation.
• Strong fundamentals in API design, distributed systems, automated testing, version control, CI/CD, observability and secure development.
• Clear communication, commercial judgment and ability to translate ambiguous business needs into feasible technical approaches.

Required skills

• Python programming.
• Experience with at least one enterprise stack: Java.NET or TypeScript/Node.js.
• Depth in a major cloud platform (AWS, Microsoft Azure or Google Cloud).
• Knowledge of enterprise data integration, SQL and vector databases.
• Experience with containerised workloads and Kubernetes.
• Familiarity with AI application frameworks (e.g., Langraph, PydanticAI) or model platforms (Azure Foundry, AWS Bedrock).