Lead Product Engineer, Enterprise AI Platform

Socket.dev; New York (NY); On-site; USD 195,000 - 275,000; Full time

Job summary

Morgan Stanley is seeking a DevGen.AI Lead Product Engineer to guide product execution across platform capabilities, reusable agents, prompts, patterns, accelerators, APIs, and adoption workflows.

You will partner with engineering, governance, SRE, security, and business stakeholders to move AI use cases from experimentation to enterprise-scale production, emphasizing responsible AI, governance, and measurable business impact.

Qualifications

• Bachelor’s or Master’s degree in a relevant field.
• 10+ years in software engineering, product engineering, or enterprise tech.
• Experience delivering enterprise-scale platforms.
• Strong communication with senior stakeholders.
• Experience with AI platforms, developer tools, and governance.

Responsibilities

• Lead DevGen.AI product execution across capabilities, agents, prompts, and patterns.
• Collaborate with engineering, governance, and security for scalable deployment.
• Balance speed, reuse, safety, and measurable business impact.
• Own intake and prioritize high-value DevGen.AI demand.
• Translate customer needs into backlog themes and platform enhancements.
• Drive lifecycle adoption from Innovate to Implement with governance gates.

Skills

Product engineering

Leadership

Communication

Cloud-native

APIs

Observability

Security

Production readiness

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

LangChain

LangGraph

Semantic Kernel

MCP

Vector search

RAG pipelines

Azure OpenAI

AWS Bedrock

Job description

Morgan Stanley is seeking a DevGen.AI Lead Product Engineer to guide product execution across platform capabilities, reusable agents, prompts, patterns, accelerators, APIs, and adoption workflows.

You will partner with engineering, governance, SRE, security, and business stakeholders to move AI use cases from experimentation to enterprise-scale production, emphasizing responsible AI, governance, and measurable business impact.