Lead AI Agent Platform Engineer (SDK & Orchestration)

JPMorganChase

Jersey City (NJ)

On-site

USD 190,000 - 240,000

Full time

5 days ago
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Job summary

JPMorganChase is seeking a Lead Software Engineer for the AI Agent Platform within Enterprise Technology, AI and Machine Learning & Data Platforms in Jersey City. You will architect and deliver the SDK and orchestration components powering enterprise agents at scale, including memory, grounding, and tool use across sessions.

Responsibilities span design, deployment, monitoring, and collaboration with product groups to achieve measurable outcomes, advancing NL2SQL and RAG capabilities while

Qualifications

  • Proven experience in Python and software engineering fundamentals.
  • Hands-on experience deploying ML/LLM systems to production.
  • Strong testing, code review, and design pattern skills.
  • Experience with prompt engineering and evaluation methods.

Responsibilities

  • Lead end-to-end delivery of the AI Agent Platform SDK and frameworks from design to production deployment.
  • Own core platform services: agent orchestration, tool calls, retrieval-augmented generation, model-serving integration.
  • Develop agent modalities including voice, document extraction, and memory across sessions.
  • Drive hill-climbing improvements for NL2SQL, RAG, and related capabilities via data and benchmarks.
  • Establish engineering standards and robust observability for reliability and performance.

Skills

Python
SDLC
Testing
Prompting
Distributed systems

Education

Bachelors degree

Tools

Docker
Kubernetes
LangGraph
LlamaIndex

Job description

JPMorganChase is seeking a Lead Software Engineer for the AI Agent Platform within Enterprise Technology, AI and Machine Learning & Data Platforms in Jersey City. You will architect and deliver the SDK and orchestration components powering enterprise agents at scale, including memory, grounding, and tool use across sessions.

Responsibilities span design, deployment, monitoring, and collaboration with product groups to achieve measurable outcomes, advancing NL2SQL and RAG capabilities while

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