Lead AI Platform Product Engineer

Morgan-Stanley; Town of Islip (NY); On-site; USD 195,000 - 275,000; Full time

Job summary

Morgan Stanley is seeking a Lead DevGen.AI Product Engineer to steer product execution, governance, and customer adoption for DevGen.AI, the firm’s enterprise AI platform. You will connect enterprise demand to capabilities, shaping reusable patterns and scalable delivery across teams.

The role demands a strong product engineering background, hands-on AI experience, and the ability to drive adoption and measurable business impact in a fast-moving, regulated environment.

Qualifications

• 10+ years in software engineering, product engineering, solution architecture, AI platforms, or enterprise tech delivery.
• Strong understanding of generative AI, LLMs, prompt engineering, and responsible AI practices.
• Ability to translate complex customer needs into reusable platform capabilities and roadmaps.
• Experience leading cross-functional teams and delivering enterprise-scale solutions.

Responsibilities

• Lead DevGen.AI product execution across platform capabilities, agents, prompts, patterns, accelerators, APIs, and adoption workflows.
• Partner with engineering, governance, SRE, and business stakeholders to move use cases from pilot to enterprise scale.
• Own intake orchestration for high-value DevGen.AI demand and translate needs into prioritized backlog themes.
• Drive adoption of Innovate Incubate Implement lifecycle with governance gates and production readiness.

Skills

Product engineering

Generative AI

APIs

Platform ownership

Education

Bachelor’s or Master’s in CS/Engineering/AI

Tools

LangChain

LangGraph

Semantic Kernel

MCP

Vector search

RAG pipelines

Azure OpenAI

AWS Bedrock

Google Vertex AI

Job description

Morgan Stanley is seeking a Lead DevGen.AI Product Engineer to steer product execution, governance, and customer adoption for DevGen.AI, the firm’s enterprise AI platform. You will connect enterprise demand to capabilities, shaping reusable patterns and scalable delivery across teams.

The role demands a strong product engineering background, hands-on AI experience, and the ability to drive adoption and measurable business impact in a fast-moving, regulated environment.