As a Data Engineering & Applied AI Software Engineer II at JPMorganChase within the Asset & Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes standard software solution, design, development, and technical troubleshooting
Writes secure and high-quality code using the syntax of at least one programming language with limited guidance - Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Hands on design and development of agentic production data platform with full stack application ownership.
- AI first mindset in developing code using Claude Code, building agents to make application/platform autonomous.
- Develop AI skills, agents, MCP server in support of product capabilities to deliver business value
- 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
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
- Formal training or certification on software engineering concepts and 2+ years applied experience
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Frontend: React or Angular with TypeScript.
- Backend: Python, Java, or Kotlin with REST or GraphQL.
- Data Engineering/Platform: Spark, Kafka, Airflow, Snowflake, and AWS.
- Platform engineering: containers, CI/CD, observability, and controlled release practices.
- Applied AI with LLMs: Claude Code, Agent, Skills, RAG, embeddings, prompt or configuration management, evaluation and guardrails, and agent tool or function calling
- Preferred financial services or Wealth Management experience, data governance or data management domain expertise, and experience evaluating and enterprise-hardening open-source software
- Bachelor’s degree required. Advanced degree is a plus