AI / ML Engineer

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 III position at the Director level, 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. Partner with the Advanced Analytics, Machine Learning, and Gen AI Platform team(s) across multiple project areas, working in collaboration with teams in India & US. The individual will 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, and contribute to the overall cloud adoption and engineering roadmap. What You’ll Do In The Role Hands‑On Engineer who acts as the catalyst in building and deploying AI Agents at scale to accelerate technology and business roadmaps 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 or real‑time used by AI Agents What You’ll Bring To The Role Experienced professional with 2+ years of experience building GenAI solutions and supporting component design, architecture, development, and operationalization of agent orchestrations at scale Agent Orchestration Frameworks: mastery of frameworks like LangChain, LangGraph, CrewAI, and Microsoft AutoGen 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 a fast‑paced and dynamic environment Good written and verbal communication skills What You Can Expect From Morgan Stanley At Morgan Stanley, you’ll find an opportunity to work alongside the best and brightest in an environment that is supportive and empowering. Our teams value creativity, collaboration, and diverse perspectives, and we offer extensive employee benefits that recognise work‑life balance and professional growth. Expected base pay rates for the role will be between $120,000 and $165,000 per year at commencement of employment. Compensation may also include commission earnings, incentive compensation, discretionary bonuses, other short and long‑term incentive packages, and various benefit programs. Equal Employment Opportunity Statement 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. For more information, please visit: #J-18808-Ljbffr Morgan Stanley