Software Engineer III - Python/ AI

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III - Python/ AI at JPMorganChase within the Commercial and Investment Bank , you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

- Build and maintain UI dashboards using React/TypeScript and backend services in the Python stack

- Design and deliver data pipelines/ETL on modern data platforms (e.g., Databricks, Snowflake)

- Execute software design, development, testing, and technical troubleshooting across the SDLC

- Ensure large language models (LLMs) are used as controlled, well-understood components of the engineering lifecycle (enterprise-approved models)

- Lead structured requirements analysis using LLM-assisted workflows to translate business and regulatory needs 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, traceability, and auditability in regulated environments

- Ensure LLM-driven systems meet enterprise reliability, resilience, and security expectations

- Coach teams on safe, compliant LLM/agent usage by documenting strengths, limitations, and risk profiles for different classes of engineering work

- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

- 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 3+ years applied experience.

- Strong Python skills, including familiarity with agentic development practices

- Experience with database design and data modeling on modern data platforms (e.g., Databricks, Snowflake)

- Hands-on experience using approved AI-assisted development tools (e.g., copilots/LLM coding assistants) to design and deliver end-to-end applications, with strong validation habits for correctness, performance, and security

- Experience developing, debugging, and maintaining code in a large enterprise environment using one or more modern programming languages and database querying languages

- Strong understanding of SDLC and agile delivery practices, including CI/CD, application resiliency, and security controls

- Strong understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs/outputs, resiliency/security expectations), including experience coaching engineers on compliant adoption

- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.

- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

- Familiarity with modern front-end technologies

- Experience in Risk and Pnl in Markets

- Exposure to public cloud, with preference for AWS

- Knowledge of Financial Markets and Products (Fixed Income, Derivatives) and Treasury concepts)