✨ AI Summary
Lead Software Engineer at JPMorgan Chase responsible for designing and building secure, high-quality production code for agentic systems and Chase AI components. The role requires 5+ years in software engineering (with 2+ years in complex scalable or agentic systems), proficiency in Java and Python, and experience with AWS, containerization, and modern API ecosystems. You will lead code reviews, mentor junior engineers, collaborate across product, design, and operations, ensure security and regulatory compliance, and advance performance, reliability, and governance of large-scale systems.
🎁 Benefits & Perks
comprehensive health care coverage, retirement savings plan, on-site health and wellness centers, backup childcare, tuition reimbursement, mental health support, financial coaching
Requirements
The role requires hands-on experience building agentic systems with LLMs/SLMs, at least 5 years in software engineering with 2+ years building complex scalable or agentic systems, and hands-on expertise in Java and Python along with modern cloud, container, and API technologies. Strong collaboration, leadership, and knowledge of agile practices are essential. Preferred experience includes distributed orchestration for LLM applications, secure integrations, safe rollout strategies, and strong security/regulatory awareness for financial services.
Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking division, you will design and build critical technology solutions across Chase AI components—including Chase Agent, Agent Operating Memory, Domain Agents, Agentic Experience Service, and Assurance.
Job responsibilities
- Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems.
- Execute software solutions, design, development, and technical troubleshooting, thinking beyond routine approaches to solve complex problems.
- Produce architecture and design artifacts for complex applications, ensuring design constraints are met by software code development.
- Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to drive continuous improvement of software applications and systems.
- Proactively identify hidden problems and patterns in data, using insights to drive improvements in coding hygiene and system architecture.
- Contribute to software engineering communities of practice and events that explore new and emerging technologies.
- Foster a team culture of diversity, opportunity, inclusion, and respect.
- Adopt and learn new technologies that positively impact agentic solutions.
- Collaborate with cross-functional teams, including product, design, and operations, to deliver end-to-end solutions.
- Lead code reviews, mentor junior engineers, and promote best practices in software engineering.
Ensure compliance with security, privacy, and regulatory requirements in all software solutions
Required qualifications, capabilities, and skills
- Hands-on experience building agentic systems using LLMs/SLMs
- 5+ years of software engineering experience, with 2+ years building complex scalable applications or agentic systems.
- Experience setting up and maintaining MCP servers and building MCP-compatible tools/adapters
- Proficient in coding in one or more languages: Java, Python; able to jump between Java and Python projects as needed.
- Proficiency building production services with either Spring AI and the Spring ecosystem (Spring Boot, Spring Security, Spring Cloud), or Python (FastAPI/Flask), with 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.
- Excellent communication and cross-functional collaboration skills.
- Experience with agile methodologies and working in fast-paced, iterative development environments.
Preferred qualifications, capabilities, and skills
- Expertise with distributed orchestration patterns for LLM applications (graph-based flows, retries, fallbacks, guardrails) and secure integration with enterprise tools and data.
- Experience with safe rollout strategies (shadowing, A/B testing, progressive exposure), human-in-the-loop review, and continuous evaluation for quality and safety, including canary rollouts.
- Knowledge of API gateways, service mesh, and multi-region high availability and disaster recovery for mission-critical services.
- Familiarity with data privacy, security best practices, and regulatory compliance in financial services.
- Experience with performance optimization, scalability, and reliability engineering for large-scale systems.
- Ability to evaluate and integrate third-party tools, libraries, and frameworks to accelerate development.
- Demonstrated leadership in technical communities, open source contributions, or industry forums.