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, which is part of the job family responsible for developing and maintaining software solutions that support business needs.
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.
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 / real-time used by AI Agents
What you'll bring to the role:
- Experienced professional with 2+ years of experience working towards building GenAI solutions & supporting components design, architecture, development, and operationalization of agent orchestrations at scale
- Agent Orchestration Frameworks: Mastery of frameworks like LangChain, LangGraph, CrewAI, and Microsoft's 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 Fast paced and Dynamic environment.
- Good written and verbal communication skills
WHAT YOU CAN EXPECT FROM MORGAN STANLEY: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 - aren't just beliefs, they 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. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. 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, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Expected base pay rates for the role will be between $120,000 and $165,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
