Analyst, P1, Software Eng I : Job Level - Analyst

Department: CPS Technology/Role/Department at Morgan Stanley Technology is the key differentiator that ensures that we manage our global businesses and serve clients on a market leading platform that is resilient, safe, efficient, smart, fast and flexible. Technology redefines how we do business in global, complex and dynamic financial markets. We have many award-winning technology platforms that help to propel our Firm's businesses to be the top in the market. Our India technology teams are based in Mumbai and Bengaluru. We have built strong techno-functional teams which partner with our offices globally taking global ownership of systems and products. We have a vibrant and diverse mix of technologists working on different technologies and functional domains. There is a large focus on innovation, inclusion, giving back to the community and sharing knowledge.

Overview We are seeking an AI Developer to design, build, and deploy production-grade Generative AI solutions, with a strong focus on?multi-agent orchestration?and?RAG-based architecture. The ideal candidate is an expert in?Python, experienced with?Lang Chain?(and/or similar agent frameworks), and hands-on with?embeddings, vectorization, and vector databases. The role also requires working knowledge of?Model Context Protocol (MCP)?to integrate tools/data sources, plus basic?React?skills to support lightweight UI experiences for AI-powered applications.

The candidate is responsible for designing and delivering end-to-end agentic AI solutions that solve real business problems, combining LLM/agent frameworks with enterprise platforms and existing application ecosystems. The candidate will define solution architectures, select and integrate appropriate technologies, and ensure alignment with enterprise architecture principles, security, scalability, and governance standards. The candidate will also analyze business processes and application flows to identify automation and augmentation opportunities, translate them into robust agent designs, and contribute to the organization's AI and architecture strategy through patterns, standards, and reusable reference implementations.

Design and implement?multi-agent GenAI solutions?(planner/executor/reviewer patterns, role-based agents, tool-using agents) for complex business workflows. Build end-to-end?RAG pipelines: ingestion, chunking, metadata strategy, embedding generation, indexing, retrieval, reranking, and grounded response generation. Develop and maintain AI services in?Python?(e.g., FastAPI), including streaming responses, structured outputs, and tool/function calling. Integrate external tools and enterprise systems using?MCP?(Model Context Protocol) and/or API-based connectors. Contribute to?LLM model development?activities where required: dataset preparation, evaluation harnesses, prompt engineering, fine-tuning/PEFT (as applicable), and benchmarking. Implement quality and safety controls: prompt-injection mitigation, output validation, privacy/PII handling, and governance-aligned logging. Collaborate with front-end developers and build basic UI components in?React?to demonstrate workflows (chat UX, agent status, citations, feedback capture). Establish engineering best practices: testing, monitoring, CI/CD readiness, documentation, and performance/cost optimization. Technical Skills Core GenAI / Agentic Strong experience building GenAI applications with?LangChain?(agents, tools, chains, retrievers, memory/state). Proven experience creating?multi-agent systems?(orchestrating multiple specialized agents; control flow, handoffs, and termination criteria). Strong understanding of?embeddings and vectorization, semantic search, and similarity metrics. RAG & Vector Databases Hands-on with vector stores. Experience with retrieval design: chunking strategies, hybrid retrieval, reranking, filtering, citations/grounding. LLM Development Experience with LLM evaluation and improvement: prompt