Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

DevGen.AI Lead Product Engineer will lead product execution, engineering enablement, and customer adoption for DevGen.AI, Morgan Stanley’s enterprise capability for turning AI experimentation into governed, reusable, production-ready business impact. The role sits at the intersection of customers, platform engineering, governance, InnerSource contributors, and divisional stakeholders. It is responsible for connecting enterprise demand to DevGen.AI capabilities, shaping reusable patterns and agents, accelerating high-value use cases, and ensuring teams can move through the Innovate → Incubate → Implement lifecycle with appropriate controls, measurement, and production readiness.

Responsibilities

Lead DevGen.AI product execution across platform capabilities, reusable agents, prompts, patterns, accelerators, APIs, and adoption workflows.
Partner with engineering, architecture, governance, SRE, security, and divisional teams to move use cases from experimentation to pilot validation and enterprise-scale implementation.
Serve as the connective tissue across product, engineering, users, governance, and executive stakeholders—balancing speed, reuse, safety, and measurable business impact.
Own intake orchestration for high-value DevGen.AI demand, ensuring teams are guided to the right capabilities, reusable assets, and delivery path.
Translate customer demand, usage data, and recurring enterprise needs into prioritized product backlog themes and platform enhancement opportunities.
Drive adoption of the Innovate → Incubate → Implement lifecycle, including feasibility validation, pilot measurement, governance gates, production readiness, and scalable launch patterns.
Build and guide rapid prototypes, POCs, reusable reference implementations, technical playbooks, and patterns that reduce time-to-value for delivery teams.
Enable responsible AI adoption by coordinating with governance stakeholders and embedding completeness, accuracy, timeliness, controls, and measurement into delivery practices.
Champion InnerSource contribution practices so reusable assets, prompts, agents, rubrics, and implementation patterns become firmwide capabilities rather than one-off solutions.
Lead community enablement through office hours, demos, onboarding support, technical guidance, documentation, and knowledge-sharing forums.
Identify opportunities to reduce duplication across teams by connecting similar use cases, promoting common patterns, and scaling best-of-breed implementations.
Track, communicate, and improve adoption, productivity, ROI, contribution, and platform impact metrics for stakeholders and senior leadership.

Requirements

Strong product engineering background with proven experience delivering enterprise platforms, developer tools, AI/LLM applications, or internal technology products.
Hands-on understanding of Generative AI, LLMs, prompt engineering, agentic architectures, RAG patterns, evaluation methods, and responsible AI delivery practices.
Ability to translate complex customer needs into reusable platform capabilities, product backlog priorities, technical patterns, and implementation roadmaps.
Experience leading engineering teams or cross-functional delivery across product, platform, architecture, security, SRE, governance, and business stakeholders.
Strong technical fluency in APIs, cloud-native engineering, platform architecture, software delivery lifecycle, observability, access control, and production readiness practices.
Demonstrated ability to build prototypes, reference implementations, technical documentation, reusable accelerators, and developer enablement materials.
Excellent communication skills with the ability to engage senior stakeholders, explain technical concepts clearly, and influence without direct authority.
Strong execution discipline, prioritization skills, and comfort operating in a fast-moving, high-demand environment with multiple concurrent use cases.
Experience working in global, matrixed, regulated, and highly collaborative enterprise technology environments.
Prior experience leading engineers, product squads, solution engineering teams, or cross-functional execution across multiple stakeholder groups.
Proven track record delivering enterprise-scale platforms or reusable technology capabilities with measurable adoption and business impact.

Skills

Generative AI
LLMs
Prompt engineering
Agentic architectures
RAG patterns
Evaluation methods
Responsible AI delivery practices
APIs
Cloud-native engineering
Platform architecture
Software delivery lifecycle
Observability
Access control
Production readiness practices
LangChain
LangGraph
Semantic Kernel
MCP
Multi-agent orchestration
Vector search
RAG pipelines
Azure OpenAI
AWS Bedrock
Google Vertex AI
Internal AI gateways
Enterprise model access/control patterns
Platform engineering
Developer experience
InnerSource/community-led development
Solution architecture
Enterprise AI enablement
Governance
Model evaluation
Risk controls
Entitlement management
Monitoring/SRE
Secure architecture
Production support in regulated environments
Business value measurement
Adoption metrics
Productivity gains
Usage analytics
Contribution metrics
ROI
Capacity creation

Location

43 countries

Work Type

Full-time

Experience Level

10+ years of experience in software engineering, product engineering, solution architecture, AI platforms, developer platforms, or enterprise technology delivery.

Education Level

Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, Information Systems, or a related technical discipline.

Salary/Compensations

$195,000 - $275,000 per year

Benefits

Attractive and comprehensive employee benefits and perks in the industry.
Opportunity to work alongside the best and the brightest.
Supported and empowered environment.
Ample opportunity to move about the business.

About the Company

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services.
The Firm's employees serve clients worldwide including corporations, governments, and individuals from more than 1,200 offices in 43 countries.
DevGenAI has been an extraordinary AI-development platform built internally inside Morgan Stanley.
With CIO-100 Aweard (2026), Banking Award Finalists (2026) and Victory of Banking Award (2025), DevGenAI is well known and street-credentialed.
Our global technology head openly amplified DevGenAI in LinkedIn.
DevGenAI core team received more than 9 USA Patents in the last 2 years, more than 8 people “First Time Patent Receivers”.
The platform enables building tech-for-tech solutions, Strats-Solutions, and appropriate business solutions (e.g., HR-solution currently in POC—DeV stage).
With more than 200 engineers contributing code, and more than 4000 PRs in an year, it is one of the most active inner-source platforms and it contributes extensively to various production solutions currently being used by our highly accomplished “User-Partners”.
At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals.
We do it in a way that’s differentiated – and we’ve done that for 90 years.
Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries.
Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences.
We are proud to support our employees and their families at every point along their work-life journey.

Equal Opportunity

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background.
Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.