Lead Software Engineer, ML Engineer for Agent Platform

JPMorgan Chase

Confirmed live 2 days ago Trusted

Quick summary

Work type
On-site
Location
Jersey City, NJ
Posted
53 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $216k
$174k most similar roles pay here $261k

This listing doesn't post a salary. Most similar roles pay $184,975–$246,150.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, ML Engineer for Agent Platform

Lead Software Engineer - ML Engineer for Agent Platform joins the Commercial and Investment Banking – Data Analytics Payments Team to build and deliver NEO, a firm-wide agent runtime platform for Payments Technology. This role involves hands-on engineering of critical components including secure execution via micro-VMs, agent-to-agent communication, memory layers, retrieval systems, and evaluation harnesses. The engineer will develop high-quality production code, implement permission-aware execution, and lead technical evaluations with external vendors. Key technologies include Python, Kubernetes, Docker, Terraform, and LLM-powered agentic systems featuring RAG architectures and vector databases. Candidates must possess expertise in AI-assisted engineering practices, CI/CD pipelines, and secure coding standards. The role addresses the challenge of building stable, scalable, and secure infrastructure for autonomous agents within a complex financial services environment while mentoring other engineers and leading communities of practice.

What you'll do

  • Build and operate core runtime components including agent execution, sandboxing via micro-VMs, and memory layers.
  • Develop secure, high-quality production code while reviewing and debugging code written by other engineers.
  • Implement permission-aware, auditable execution for agents with fine-grained authorization and runtime policy checks.
  • Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
  • Lead evaluation sessions with external vendors and internal teams to probe architectural designs and technical feasibility.
  • Identify opportunities to automate the remediation of recurring issues to improve system operational stability.
  • Mentor senior engineers and lead communities of practice to promote leading-edge technologies across the organization.

What we're looking for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Advanced proficiency in one or more programming languages, including a strong requirement for Python.
  • Hands-on experience delivering system design, application development, testing, and operational stability.
  • Demonstrated experience leading the use of approved AI-assisted software development tools and coaching others on safe adoption.
  • Experience building LLM-powered or agentic systems, including tracing, evaluations, and guardrails.
  • Proficiency in all aspects of the Software Development Life Cycle, including CI/CD, application resiliency, and security.
  • Practical cloud native experience with production Kubernetes expected.
  • In-depth knowledge of the financial services industry and their IT systems.
  • Exposure to LLMs, RAG architectures, vector databases, and embedding-based retrieval (preferred).
  • Experience with agent protocols, multi-agent orchestration, or sandboxed code execution (preferred).
  • Proficiency in Infrastructure as Code (Terraform) and containerized deployments (preferred).

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