Senior Lead AI Engineer

About the role

Oliver Wyman is seeking a senior technology leader to design and deliver secure, production‑grade AI solutions that integrate with enterprise applications, data platforms and operational controls. This applied engineering position focuses on practical AI implementation rather than research.

Key responsibilities

• Lead AI solution delivery from problem framing through architecture, implementation, production release and continuous improvement.
• Create pragmatic enterprise architectures that connect AI capabilities with existing APIs, data platforms, identity, security and operational controls.
• Develop critical components, set coding and testing standards, and guide teams on quality, cost, speed and maintainability trade‑offs.
• Design and implement agentic applications, retrieval‑augmented generation, model routing, caching, vector databases and observability pipelines for enterprise‑scale AI.
• Define evaluation criteria, test sets and feedback loops to measure accuracy, reliability, safety, latency, cost and business impact.
• Collaborate with security, privacy, risk and legal partners to embed responsible AI guardrails and auditability.
• 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 track record 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 influence architecture and engineering standards across multidisciplinary teams without relying solely on formal authority.

Required skills

• Python programming
• Experience with at least one enterprise stack: Java.NET or TypeScript/Node.js
• Deep knowledge of a major cloud platform (AWS, Azure or Google Cloud)
• Understanding of enterprise data integration, SQL and search/retrieval concepts
• Familiarity with AI application frameworks (e.g., Langraph, PydanticAI) or model platforms (Azure Foundry, AWS Bedrock)
• Container orchestration with Kubernetes and infrastructure‑as‑code practices