Developer Engagement Engineer - VP

Morgan Stanley•New York, NY

2d•$155,000 - $215,000

About The Position

We are seeking a hands-on Developer Engagement Engineer to join the Firmwide developer tools group, MSDE. In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Software Engineering position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs. Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals. MSDE is responsible for shaping the SDLC within Morgan Stanley by implementing the tools, systems, and processes used by 25,000+ developers in the Firm for software development and deployment. This role sits at the intersection of software engineering, developer experience, and AI coding tool adoption. You'll help ensure developers don't just get access to agentic AI capabilities — they use them well, safely, and meaningfully in real workflows. You'll work with engineering teams, platform owners, risk partners, and senior technology leaders to scale adoption across the firm. The ideal candidate is a hands-on developer who enjoys helping others succeed, explains technical concepts clearly, and thrives in ambiguity and fast-moving change.

Requirements

Software development experience with exposure to modern engineering workflows (PRs, CI/CD, developer tooling)
Practical experience with AI coding tools (e.g., GitHub Copilot, Codex, Cursor, Claude Code)
Ability to evaluate where AI tools add value — and where they introduce risk
Comfort leading demos, workshops, and enablement sessions for varied audiences
Clear, credible written and verbal communication
Ability to synthesize feedback and usage patterns into recommendations
Skill in building trust with engineers by being honest, practical, and technically grounded
Genuine enthusiasm for AI coding tools and curiosity about how developers work
Bias toward action, experimentation, and practical outcomes
Comfort with evolving tools, policies, and best practices
Collaborative approach across teams, regions, and experience levels

Nice To Haves

Familiarity with enterprise SDLC practices or regulated technology environments is a plus

Responsibilities

Engage Developers: Run demos, workshops, office hours, and enablement sessions
Help teams identify practical use cases for AI coding tools across coding, testing, refactoring, documentation, and code review
Create reusable examples, patterns, and guidance that accelerate adoption
Gather developer feedback and translate it into actionable insights for platform and product teams
Drive Practical Adoption: Develop clear guidance for responsible, productive use of AI coding tools
Help teams distinguish where agentic AI accelerates work from where human judgment remains essential
Surface and share successful usage patterns across teams and business areas
Partner with engineering leaders to identify blockers and define what good usage looks like in a regulated enterprise
Advocate for Developers: Represent the developer perspective in discussions with platform, tooling, risk, training, and leadership teams
Foster a community of AI coding tool champions and encourage cross-team knowledge sharing
Create Enablement Content: Guides, FAQs, playbooks, demo scripts, workshop materials, and short-form updates for engineers and senior stakeholders
Prioritize clarity and usefulness over corporate polish
Shape the Adoption Strategy: Contribute to rollout planning, usage analysis, and continuous improvement
Identify patterns, success stories, and risks to inform training, communications, and support models