Lead Software Engineer - Python, Full Stack / AI

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 - Python, Full Stack / AI at JPMorgan Chase in Commercial and Investment Bank's Treasury Technology you will lead the build out of an end-to-end data platform to manage Capital, Liquidity, Balance sheet, Funding and billing (Transfer pricing).

You will develop and enhance applications critical to the business, working closely with Treasury, Finance, Trading, Sales, and Quantitative Research teams.

Your expertise in Python and agentic development will drive automation and innovation.

You will contribute to a global platform, ensuring stability and delivering high-quality solutions.

This role offers the chance to make a meaningful impact in a fast-paced, collaborative environment.

Job Responsibilities


* Full Stack development of UI Dashboard in React/Typescript and servers in the python stack.


* Deliver data pipelines and ETL on data platforms such as Databricks and Snowflake


* Executes software solutions, design, development, and technical troubleshooting


* This role ensures that large language models (LLMs)-including models such as Claude, ChatGPT, and comparable enterprise-approved models-are used as controlled, well-understood components of the software engineering lifecycle.


* Lead the use of LLMs for structured requirements analysis, including translating business and regulatory requirements into clear technical specifications.


* Establish best practices for prompt-driven design and development, treating prompts as versioned, reviewable engineering artifacts.


* Ensure prompt strategies support determinism, reproducibility, and traceability in regulated environments.


* Ensure LLM-driven systems meet enterprise reliability and resilience expectations.


* The role supervises how LLM-assisted and agent-driven development is performed, ensuring that model strengths, limitations, and risk profiles are understood, documented, and appropriately applied across different classes of software work


* 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 of applied experience


* Strong Python skills and familiarity with age...