JP Morgan Chase

Runs a consumer bank and an investment bank

Lead Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours

Full-timeSan Francisco, CA, USA$156.8k - $215k /yrIn-person

About the Job

Requirements

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Strong proficiency in Java and strong working experience with Python.
Strong architecture and design skills across systems with sound engineering judgment.
Strong engineering fundamentals, including object-oriented design, design patterns, SOLID principles, and testing-driven development.
Strong integration and data fundamentals, including SQL/PL-SQL and event messaging such as MQ/Kafka.
Experience operating production services with continuous integration and continuous delivery, observability, and reliability best practices.
Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practice.
Ability to create roadmaps and milestones, manage dependencies, and execute effectively in agile or Scrum environments.
Track record of mentoring engineers, leading reviews, and raising engineering standards across a team.
Strong communication and collaboration skills across distributed, cross-functional stakeholders.

Responsibilities

Lead end-to-end design, implementation, and operation of complex platform features and integrations.
Create technical roadmaps and milestones, drive predictable delivery, and improve team processes continuously.
Develop assistant skills and tool functions with clear interfaces, schemas, validation, error handling, and observability.
Stand up and operate Model Context Protocol servers and integrations and use agent patterns to accelerate delivery.
Establish evaluation checks, guardrails, and monitoring so AI behavior is accurate, safe, and verifiable.
Drive data readiness and integration practices, including modeling, pipeline alignment, and quality controls, to underpin AI outcomes.
Uphold software development life cycle rigor through secure coding, code reviews, automated testing, continuous integration and delivery, and production readiness.
Mentor junior engineers in technical and soft skills, delegate effectively, and unblock delivery through technical leadership.
Partner with product and analyst stakeholders on estimates, delivery plans, dependencies, and outcomes.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while establishing validation standards and promoting reuse of effective patterns across the team.
Apply knowledge of software development life cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to improve the value realized by automation.

Desired Qualifications

ServiceNow experience, including familiarity with the ServiceNow data model.
Experience using AI-assisted development tools responsibly with strong engineering judgment and secure coding practices.
Experience with Model Context Protocol operations patterns, including authentication and authorization, logging and traceability, rate limiting, versioning, and safe rollout.
Experience designing AI agents with grounding or retrieval-augmented generation patterns, deterministic fallbacks, prompt and version management, and evaluation harnesses.
Understanding of data privacy and security considerations for agent workflows, including data minimization, secrets management, least privilege, and auditability.
Experience in AWS or other public cloud platforms.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Infrastructure Platforms Digital Workflows Product Line, you will lead delivery of high-quality technical solutions, drive roadmaps and agile execution, mentor engineers, and implement AI-enabled engineering capabilities (including tool functions/skills and MCP servers/agents) within governance, security, and risk controls.

Job responsibilities

Lead end-to-end design, implementation, and operation of complex platform features and integrations.
Create technical roadmaps and milestones; drive predictable delivery and continuous team process improvement.
Develop assistant skills/tool functions with clear interfaces, schemas, validation, error handling, and observability.
Stand up and operate MCP (Model Context Protocol) servers/integrations and agent patterns to accelerate delivery.
Establish evaluation checks, guardrails, and monitoring so AI behavior is accurate, safe, and verifiable.
Drive data readiness and integration practices (modeling, pipelines alignment, quality controls) underpinning AI outcomes.
Uphold SDLC rigor: secure coding, code reviews, automated testing, CI/CD, and production readiness.
Mentor junior engineers (technical and soft skills), delegate effectively, and unblock delivery through technical leadership.
Partner with product and analyst stakeholders on estimates, delivery plans, dependencies, and outcomes.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience
Strong proficiency in Java and strong working experience with Python.
Strong architecture and design skills across systems with sound engineering judgment.
Strong engineering fundamentals (OOD, design patterns, SOLID) and a quality-first mindset (testing/TDD).
Strong integration and data fundamentals (SQL/PL-SQL; event messaging such as MQ/Kafka).
Experience operating production services with CI/CD, observability, and reliability best practices.
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practice.
Ability to create roadmaps/milestones, manage dependencies, and execute effectively in agile/scrum environments.
Track record of mentoring engineers, leading reviews, and raising engineering standards across a team.
Strong communication and collaboration skills across distributed, cross-functional stakeholders.

Preferred qualifications, capabilities, and skills

ServiceNow experience (including familiarity with the ServiceNow data model).
Experience using AI-assisted development tools responsibly with strong engineering judgment and secure coding practices.
Experience with MCP operations patterns (authN/Z, logging/traceability, rate limiting, versioning, safe rollout).
Experience designing AI agents with grounding/RAG patterns, deterministic fallbacks, prompt/version management, and eval harnesses.
Understanding of data privacy/security considerations for agent workflows (data minimization, secrets management, least privilege, auditability).
Experience in AWS or other public cloud platforms.

FEDERAL DEPOSIT INSURANCE ACT

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.

Base Pay/Salary: San Francisco,CA $156,750.00-$215,000.00

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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