Software Engineer III - Data Engineer/Applied AI (LLMs)
JPMorgan Chase · Plano, United States · 1mo ago
SeniorOn-siteSoftware Engineering
J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.
Our Asset and Wealth Management division is driven by innovators like you who are driven to create technology solutions that make us work more efficiently and help our businesses grow. It’s our mission to efficiently take care of our clients’ wealth, helping them get, and remain properly invested. Our team of agile technologists thrive in a cloud-native environment that values continuous learning using a data-centric approach in developing innovative technology solutions.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Data Engineering & Applied AI Software Engineer III 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
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 3+ 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 qualifications, capabilities, and skills:
- 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