VP, Agentic AI Architect & Technical Product Lead

Morgan-Stanley; Alpharetta (GA); On-site; USD 150,000 - 230,000; Full time

Job summary

Morgan Stanley is seeking an innovative Agentic AI Forward Deployed Engineer (FDE) at Lead VP level in Alpharetta, GA. You will design multi-agent architectures, implement human-in-the-loop handoffs, and scale agentic workflows across engineering teams to drive measurable business impact.

You will coach squads on prompting, tool usage, and governance while delivering hands-on prototypes and high-performance code within hybrid cloud environments using Docker, Kubernetes, and modern AI toolchains.

Qualifications

• 7–12 years of overall experience in distributed systems, with at least 3 years as Lead Engineer/Technical Architect.
• Experience in designing for microservices, fault tolerance, high performance, and low-latency systems.
• Proficiency in Java, C#, or TypeScript; Python proficiency preferred.

Responsibilities

• Design multi-agent architectures beyond basic Q&A; enable autonomous, externally-enabled problem solving with external APIs.
• Lead the transition of engineering teams from developers to system architects; build agentic workflows and guardrails.
• Coach engineering squads on prompting, evaluating agent outputs and safe deployment of enterprise AI solutions.
• Hands-on coding to prototype frameworks, tools, and high-performance code within a scalable SDLC harness.

Skills

Java

C#

TypeScript

Python

Distributed systems

Microservices

Low latency

Cloud (AWS/Azure)

Kubernetes

LLM fundamentals

Tools

Docker

Kubernetes

Copilot

OpenAI Codex

Claude Code

LangGraph SDK

Claude SDK

Job description

Morgan Stanley is seeking an innovative Agentic AI Forward Deployed Engineer (FDE) at Lead VP level in Alpharetta, GA. You will design multi-agent architectures, implement human-in-the-loop handoffs, and scale agentic workflows across engineering teams to drive measurable business impact.

You will coach squads on prompting, tool usage, and governance while delivering hands-on prototypes and high-performance code within hybrid cloud environments using Docker, Kubernetes, and modern AI toolchains.