below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$173,950–$246,862.
Based on 240 similar postings.
Employer
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As a Senior Lead Software Engineer - ML Engineer for Agent Platform, you will join the Commercial and Investment Banking – Data Analytics Payments Team to build and run NEO, the firm's agent runtime platform for Payments Technology. You will own the end-to-end architecture for secure execution, agent-to-agent communication, memory layers, and evaluation infrastructure. Your daily work involves developing high-quality production code, setting engineering standards, and designing permission-aware execution models using OpenFGA and OPA/Rego. You will utilize Python, Go, or Rust, alongside Kubernetes, Docker, and Terraform. The role requires expertise in micro-VMs like Firecracker, Model Context Protocol, and RAG architectures. You will solve complex problems regarding secure, scalable agent orchestration and responsible AI use within a regulated financial services environment, while mentoring engineers and leading communities of practice.
Own the end-to-end architecture of the NEO agent runtime, including secure execution, communication, and memory layers.
Develop secure production code and establish coding and design standards for all teams building on the platform.
Define permission-aware execution models using fine-grained authorization and runtime policies for regulated environments.
Drive the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
Identify and automate the remediation of recurring issues to improve the operational stability of the platform.
Lead evaluation sessions with vendors and internal teams to probe architectural designs and technical credentials.
Mentor senior engineers and lead communities of practice to promote the use of leading-edge technologies.
What we're looking for
Formal training or certification in software engineering concepts and 5+ years of applied experience.
Hands-on experience delivering system design, application development, testing, and operational stability for production platforms or distributed systems.
Advanced proficiency in Python and a systems language such as Go or Rust.
Demonstrated experience building or operating LLM/agent systems in production, including tracing, evaluations, and guardrails.
Strong understanding of responsible AI use, data sensitivity, and secure handling of inputs/outputs in engineering workflows.
Proficiency in all aspects of the Software Development Life Cycle, including CI/CD, application resiliency, and security.
Practical cloud-native experience with production Kubernetes and in-depth knowledge of financial services IT systems.
Experience with micro-VMs, agent protocols, distributed memory systems, or Infrastructure as Code (preferred).
Python
Agentic AI
LangGraph
CrewAI
AWS
Terraform
Generative AI
Retrieval-Augmented Generation
Vector Search
Distributed Systems
Site Reliability Engineering
infrastructure-as-code
Observability
Software Development Life Cycle