Senior Lead Software Engineer - Agentic AI/Java/Python
Salary not listed • Plano, TX, United States • Full-time
Posted 9d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
About the job
As a Senior Lead Software Engineer at JPMorgan Chase, you will be a key member of an agile team focused on enhancing, building, and delivering cutting-edge technology products. You will design and develop critical technology solutions within Chase AI components, including Chase Agent, Agent Operating Memory, Domain Agents, Agentic Experience Service, and Assurance. This role involves solving complex problems, creating secure and high-quality production code, and producing architecture and design artifacts for sophisticated applications. You will also analyze diverse datasets to drive improvements, adopt new technologies, and collaborate with cross-functional teams to deliver end-to-end solutions while ensuring compliance with all regulatory requirements. A significant aspect of this role is driving the adoption of enterprise-authorized AI-assisted engineering practices to enhance code quality, delivery speed, and operational outcomes.
Responsibilities
- Design and build critical technology solutions across Chase AI components.
- Execute software solutions, design, development, and technical troubleshooting for complex problems.
- Create secure, high-quality production code and maintain synchronous algorithms.
- Produce architecture and design artifacts for complex applications.
- Gather, analyze, and synthesize data from large datasets to drive software application improvements.
- Identify hidden problems and patterns in data to improve coding hygiene and system architecture.
- Contribute to software engineering communities of practice and explore emerging technologies.
- Adopt and learn new technologies that positively impact agentic solutions.
- Collaborate with cross-functional teams (product, design, operations) to deliver end-to-end solutions.
- Ensure compliance with security, privacy, and regulatory requirements.
- Drive team adoption of AI-assisted engineering practices for improved code quality, delivery speed, and operational outcomes.
- Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities.
Requirements
- 5+ years of applied software engineering experience with 2+ years building complex scalable applications or agentic systems.
- Hands-on experience building agentic systems using LLMs/SLMs.
- Experience setting up and maintaining MCP servers and building MCP-compatible tools/adapters.
- Proficient in Java and/or Python.
- Proficiency building production services with Spring AI or the Spring ecosystem (Spring Boot, Spring Security, Spring Cloud), or Python (FastAPI/Flask), including typed contracts, testing, and packaging.
- Solid AWS background with working knowledge of ECS or EKS, containerization (Docker), and CI/CD (GitHub Actions/Jenkins/CodeBuild).
- Strong API design skills (REST/OpenAPI; gRPC) and familiarity with observability stacks (e.g., Splunk, CloudWatch, Prometheus/Grafana, OpenTelemetry).
- Practical understanding of LLM patterns: function calling/tools, RAG, prompt management, context windows, token budgeting, and safety guardrails.
- Strong testing culture: unit/integration tests, load tests, and evaluation datasets for agents.
- Demonstrated experience leading effective use of approved AI-assisted software development tools and setting team expectations for validating AI outputs.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Experience coaching engineers on safe, compliant adoption within delivery practices.