We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Commercial & 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
- Executes software solutions across design, development, testing, and technical troubleshooting for AI/ML and agentic systems, thinking beyond conventional approaches to decompose problems into agent plans, tools, Skills, and workflows.
- Builds and maintains secure, high-quality production code for agent runtimes and services, including prompt/tool orchestration, state management, memory patterns, routing, and fallback strategies.
- Produces architecture and design artifacts for complex applications (e.g., multi-agent systems, Agentic RAG pipelines, evaluation harnesses) and remains accountable for ensuring design constraints are met in implementation.
- Develops Agentic RAG solutions: ingestion, chunking/indexing, embedding strategies, retrieval/reranking, citations/attribution patterns, and grounding + hallucination mitigations.
- 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.
- Integrates agents with enterprise systems via APIs and tool interfaces, including MCP-based connectors, ensuring least privilege, auditability, and safe action execution.
- Gathers, analyzes, and synthesizes insights from large, diverse datasets to build AI features, telemetry, and dashboards for quality, drift, latency, reliability, and cost. Implements model/agent evaluations (offline + online): golden sets, regression testing, adversarial testing, safety testing, and human-in-the-loop review flows.