Developer Engagement Lead – AI Coding Tools

Morgan Stanley

Developer Engagement Lead for AI Coding Tools at Morgan Stanley. Collaborating with engineering teams to enhance productivity and maximize quality in software development.

Posted 7/31/2026full-timeMontreal • 🇨🇦 CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI coding tools and software development practices, with a strong focus on enabling developer productivity and fostering collaboration across engineering teams. Capable of translating developer feedback into actionable insights while promoting responsible AI usage in regulated environments.

Highest-signal resume keywords

AI Coding Tools ExperienceSoftware Development Lifecycle (SDLC) FamiliarityStrong Presentation SkillsExcellent Communication SkillsCollaboration with Engineering Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software DevelopmentCI/CDPull RequestsAI Coding ToolsDeveloper ToolingUsage AnalysisBest Practices DevelopmentFeedback SynthesisSuccess Measures DefinitionAdoption Strategy Contribution

Soft Skills

Facilitation SkillsRelationship BuildingCuriosityAdaptabilityBias Toward Action

Tools & Technologies

GitHub CopilotCodexCursorClaude Code

Industry Keywords

Regulated Technology EnvironmentsEnterprise Software DevelopmentDeveloper ProductivityAI AdoptionEmerging Opportunities

Tech Stack

Tools & technologies

SDLC

About the role

Key responsibilities & impact

Lead demos, workshops, office hours, and enablement sessions to help developers effectively adopt AI coding tools
Partner with engineering teams to identify practical use cases for AI across software development, testing, refactoring, documentation, and code review activities
Develop reusable examples, best practices, and guidance that accelerate adoption and improve developer productivity
Gather and synthesize developer feedback, translating insights into actionable recommendations for platform, tooling, and product teams
Establish clear guidance for the responsible and effective use of AI coding tools within a regulated enterprise environment
Partner with engineering leaders to remove adoption blockers, define success measures, and promote proven usage patterns across teams
Advocate for developer needs by collaborating with platform, risk, training, tooling, and leadership stakeholders, while fostering a network of AI champions
Contribute to adoption strategy through enablement content, rollout planning, usage analysis, and the identification of emerging opportunities, risks, and success stories

Requirements

What you’ll need

At least 6+ years of software development experience with exposure to modern engineering workflows, including pull requests, CI/CD, and developer tooling
Hands-on experience with AI coding tools such as GitHub Copilot, Codex, Cursor, Claude Code, or similar technologies
Ability to assess where AI coding tools drive value and where additional controls, oversight, or human judgment are required
Familiarity with enterprise software development lifecycle (SDLC) practices and regulated technology environments
Strong presentation and facilitation skills, with the ability to lead demos, workshops, office hours, and enablement sessions for diverse audiences
Excellent written and verbal communication skills, with the ability to synthesize feedback and usage trends into practical recommendations
Proven ability to build credibility and trusted relationships with engineers through a practical, technically grounded approach
Enthusiasm for AI-powered developer tools, combined with a collaborative mindset, curiosity, adaptability, and a bias toward action and experimentation

Benefits

Comp & perks

Ample opportunity to move about the business for those who show passion and grit in their work
Attractive and comprehensive employee benefits and perks in the industry