Principal AI App Dev Engineer Vice President

We are seeking an innovative Agentic AI Forward Deployed Engineer (FDE) to build the next generation of autonomous AI systems.

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 Lead Technical Product Owner position at Vice President level which is part of the job family responsible for defining the product vision prioritizing features and ensuring the successful delivery of high-quality technical solutions.

What youll do in the role:

You will design multi-agent architectures that move beyond simple question-answering enabling AI systems to break down problems use external APIs iterate through feedback loops and operate independently to drive measurable business impact. You will enable transition of engineering teams from developers into system architects. Instead of writing raw code your focus will be on creating coding/testing agents and setting up human-in-the-loop or autonomous feedback harnesses and scaling these capabilities across the organization.

• Agent Architecture: Design and build multi-agent frameworks. Implement human-in-the-loop handoffs logging and guardrails to ensure agents comply with data protection and governance standards

• Agent-first engineering loop: Design and build agent skills tools for desktop coding agents to improve engineering productivity. accelerate SDLC reduce defects / rework and improve delivery quality through agentic workflows

• Evangelism & Coaching: Act as a trusted advisor coaching engineering squads on effectively prompting reviewing and evaluating agent outputs. Drive enterprise AI adoption safely

• Hands-on programming to develop high performance code implement application frameworks and develop prototypes to showcase new technology opportunities

What youll bring to the role:

• Overall experience between 7-12 years. Minimum 3 years in a role as Lead Engineer/Technical Architect designing for Distributed applications Microservices architecture Fault tolerance and recovery Performance Engineering Scaling Low latency application design Asynchronous programming

• Languages Proficient in atleast one of Java or C# or Typescript/ReAct. Intermediate level Python

• Infrastructure - Comfortable shipping production grade systems on Hybrid cloud infra (Docker K8s AWS or Azure).

• AI Foundational: LLM fundamentals (encoder decoder and encoder-decoder models; fine-tuning vs. prompt-tuning vs. LoRA); Prompt engineering (zero-shot few-shot and chain-of-thought prompting; prompt testing and optimization); Vector databases (for embedding storage and similarity search); Embedding models (selection generation and dimensionality considerations).

• Agentic SDLC Harness: Design specialized SDLC agent harness loops (requirements architecture coding and testing agents) and manage the interaction and context-sharing between them. Platform Integration (Embed agentic workflows natively into the existing developer ecosystem CI/CD pipelines version control and test harnesses).

• Copilot/Open AI Codex/Claude Code: Leverage hands-on familiarity with Copilot/OpenAI Codex or Claude Code to optimize model prompting tool usage context construction developing custom skills and system prompts to improve task solve rates

• LangGraph/OpenAI SDK/Claude SDK: Build autonomous AI agents with Conversational state Tool calling Sub agent orchestration

• Agentic AI: Autonomous agent concepts (multi-step reasoning goal decomposition self-reflection loops and replanning strategies); Tool-oriented execution (agents calling APIs executing scripts interacting with knowledge bases or triggering workflows); Safety and governance (guardrails grounding hallucination prevention and ethical AI use); Agent evaluation (reasoning accuracy success/failure patterns Efficiency metrics and Evaluation metrics such as accuracy F1-score or perplexity); MCP server concepts (architecture for agent communication and orchestration request/response flows streaming data multi-agent coordination and contextual state management); Agentic AI architecture internals (planner executor memory store tool registry event loop orchestration layers schedulers task prioritization failure recovery and multi-agent collaboration patterns).

• RAG: RAG architecture (retrieval pipelines context injection and grounding of LLM outputs); document chunking and indexing (splitting strategies token limits and indexing performance); Query processing (rewriting filtering and ranking retrieved documents); Evaluation and latency optimization (measuring retrieval accuracy and reducing end-to-end response time).

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 thats differentiated and weve 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 - arent just beliefs they guide the decisions we make every day to do whats best for our clients communities and more than 80000 employees in 1200 offices across 42 countries. At Morgan Stanley youll 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. Theres also ample opportunity to move about the business for those who show passion and grit in their work.

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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.

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