Lead Software Engineer-AI

Job Description

As a Lead Software Engineer - AI, you will build and ship production-grade, multi-agent AI systems used daily by thousands of engineers.

You'll work on an applied AI platform that automates key stages of the software delivery pipeline-from PRD through architecture, implementation, QA, security, and retrospective-at enterprise scale.

You will own agent capabilities end-to-end, with a focus on reliability, evaluation, observability, and cost-per-session.

This is not a research or data science role-you will engineer production systems that consistently follow specifications.

Job Responsibilities


* As a Lead Software Engineer-AI with CCB at JPMorgan Chase you will develop complex and scalable frameworks using appropriate software design, including durable and reusable frameworks leveraged across teams and functions.


* Develops secure and high-quality production code, and reviews and debugs code written by others; engineers systems with clear failure modes, retry strategies, and robust operational behavior.


* Leads cross-functional teams on technological matters within domain of expertise while acting as the function's go-to subject matter expert.


* Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies, including pragmatic AI engineering practices.


* Builds and maintains evaluation and quality mechanisms to detect regressions, measure specification/acceptance-criteria compliance, and surface behavior changes across model or dependency updates.


* Influences leaders and senior stakeholders across business, product, and technology teams.

Qualifications


* Formal training or certification on software engineering concepts and 5+ years applied experience.


* Hands-on practical experience delivering system design, application development, testing, and operational stability.


* Proficient in one or more programming language(s) (e.g., Python and/or TypeScript; able to build CLI tooling, API integrations, and data pipelines).


* Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines (including designing multi-step AI workflows: sequential chains, parallel fan-out, conditional routing, and human-in-the-loop checkpoints).


* Knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines.

(e.g., cloud, artificial intelligence / applied LLM systems, machine learning, mobile, etc.).


* Experience with agent frameworks (e.g., LangChain, LlamaIndex, AutoGen, CrewAI, or homegrown) and clear opinions on their tradeoffs.


* Demonstrated experience building systems on top of LLM APIs (endpoint integration, streaming, tool/function calling, and context management).


* Ability to present and effectively communicate with Senior Leaders and Executiv...