Sr AI​/ML Engineer - Executive Director

Position: Sr AI / ML Engineer - Executive Director
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. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic.

Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools.

Our insights, our applications and infrastructure give a competitive edge to clients' businesses-and to our own.

This role will partner with the Advanced Analytics, Machine learning and Gen AI Platform team(s), across multiple project areas, and work in collaboration with team(s) in India & US. The individual would be responsible for building autonomous systems that can reason, use tools, and complete multi-step tasks using LLMs/Reasoning models, build calibration scoring and guardrails for agent accuracy. The person would also be part of the overall cloud adoption and engineering roadmap and ensure scalable, agile and robust architecture and implementation.

Additionally, should be able to work in a dynamic environment with limited or no supervision and should be able to knowledge-share across other team members. Should be comfortable and manage time working with global team on multiple initiatives.

Responsibilities:

* Sr Hand-On Engineer who acts as the catalyst in building and deploying AI Agents at scale to accelerate technology and business roadmaps

* Collaborate across multiple peer divisions to get alignment on AI Solutions demonstrate with POCs the "Art of the possible" and accelerate adoption

* Evaluate state-of-art ML and Gen AI centric technologies and prototype solutions to improve our architecture and platform

* Design, Implement and Operationalize distributed, scalable, and reliable data flows that ingest, process, store, and access data at scale in batch / real-time used by AI Agents

Primary Skills /

Qualifications:

* Experienced professional with overall 15+ years of IT experience… out of which specifically 10+ years of experience working towards building ML & GenAI solutions & supporting components design, architecture, development, and operationalization and agent orchestration at scale.

* Agent Orchestration Frameworks:
Mastery of frameworks like Lang Chain, Lang Graph, CrewAI, and Microsoft's Auto Gen to build multi-agent workflows.

* LLM Implementation:
Deep expertise in LLM APIs (OpenAI, Anthropic, AWS Bedrock), prompt engineering (Chain-of-Thought), and fine-tuning for specific agentic behaviors.

* Memory & Context Management:
Ability to implement complex memory systems, including vector databases (Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) pipelines.

* Tool-Calling & APIs:
Proficiency in integrating external APIs as agent "tools," including function calling and error handling for malformed model outputs.

* Languages & Backend:
Expert-level Python (mandatory), often paired with FastAPI, Node.js, or Go. Familiarity with Docker and Kubernetes for containerized deployment is standard.

* Understanding of applied Machine Learning (End-to-End) Lifecycle and Operationalizing ML models in Production (MLOps)

* Ability to work in Fast paced and Dynamic environment.

* Good written and verbal communication skills

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

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