Agentic AI Engineer

Context: Vice President–level Agentic AI Engineer role in Morgan Stanley’s Institutional Securities Technology Research Technology team, focused on rapid prototyping and production delivery of governed, resilient GenAI and agentic solutions for the research department.

Responsibilities

• Maintain regular communication with product leads across the technology organization; discuss improvement opportunities for existing and future solutions.
• Partner with business stakeholders and the GenAI Infrastructure Lead to identify, prioritize, and progress high-value Research AI and agentic AI use cases.
• Translate strategic business objectives into AI initiatives, delivery plans, and measurable outcomes.
• Lead rapid prototyping to test ideas, validate technical feasibility, and demonstrate business value quickly.
• Design, build, and deploy scalable, production-ready GenAI and agentic AI solutions alongside engineering teams.
• Collaborate with engineering leads to integrate AI capabilities into existing applications and workflows.
• Work with enterprise infrastructure and platform teams to define architecture, services, and controls needed for AI solutions.
• Ensure solutions meet enterprise standards across scalability, reliability, security, observability, and governance.
• Provide hands-on technical leadership across LLMs, RAG, agent orchestration, tool integration, and workflow automation.
• Advise business stakeholders on technical options, limitations, risks, costs, and implementation trade-offs.
• Coordinate execution across business, application development, infrastructure, data, security, and governance teams.

Requirements

• Ability to manage multiple functions or guide junior staff and initiatives.
• Advanced understanding of business line and discipline, with some knowledge of the competitive environment and related disciplines.
• Experience developing scalable solutions using Python and Java; write optimized, clean, production-grade code.
• Experience building systems that comply with regulatory standards.
• Capability to influence beyond immediate teams to shape engineering standards and governance models.
• Experience engaging in multi-year, high-visibility programs driven by business and regulatory needs.
• Hands-on experience with Generative AI, coding assistants, and LLMs for improving software development and building AI-native applications.
• Experience designing, developing, deploying, and integrating MCP servers with AI agents and enterprise applications.
• Familiarity with vector databases and semantic search technologies, including MongoDB, Redis, or similar vector stores.
• Experience with containers, pipelines, Linux, and shell scripting.
• Hands-on experience with AI agent orchestration frameworks such as LangChain/LangGraph, Claude Agent SDK, OpenAI Agents SDK, or equivalent frameworks.
• Ability to utilize generative coding assistants and LLMs embedded into applications.
• Use enterprise-grade DevOps, CI/CD, and observability tools.
• Excellent analytical, communication, and stakeholder management skills across engineering, product, architecture, security, and business teams.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline.

Technologies

• Python, Java
• Generative AI, LLMs, RAG
• Agent orchestration, tool integration, workflow automation
• MCP servers
• MongoDB, Redis, vector databases, semantic search technologies
• Containers, pipelines, Linux, shell scripting
• LangChain, LangGraph, Claude Agent SDK, OpenAI Agents SDK
• DevOps, CI/CD

Location: New York, NY (onsite)

Salary: USD 155,000 - 215,000 per yearly