We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Lead Software Engineer at JPMorgan Chase within Commercial & Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading AI-enabled technology products in a secure, stable, and scalable way. You will own the end-to-end lifecycle of AI systems — from rapid prototyping and prompt engineering through to production deployment, monitoring, and continuous improvement. You will apply deep technical expertise in agentic architectures, LLM orchestration, and modern AI frameworks to tackle a diverse array of challenges that span multiple technologies and applications.
Job Responsibilities:
- Build and productionize agentic AI solutions including agents, orchestrators, tool/function integrations, workflow/state management, and guardrails
- Design and develop Python and Java services (microservices and shared libraries) with strong API contracts and domain-driven design where applicable
- Architect and manage data pipelines, embeddings, and vector stores that power RAG and other AI capabilities, including prompt versioning, templating, and optimization for reliability
- Build evaluation and observability frameworks to monitor AI system performance, including hallucination detection, latency, accuracy, and user feedback loops
- Deliver AI-enabled business UI experiences in partnership with product and UX teams, translating wireframes and design specifications into polished, production-ready interfaces that ensure usability, performance, responsiveness, and accessibility
- Establish and maintain MLOps practices for AI model deployment, including CI/CD pipelines, model versioning, and infrastructure-as-code for AI workloads
- Collaborate with security, risk, and controls partners to ensure solutions meet governance and compliance expectations for AI-enabled systems
- Drive decisions that influence product design, UI/UX direction, application functionality, and technical operations, applying creative problem-solving to tackle challenges beyond routine approaches
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 8+ years of applied experience, with demonstrable depth in AI/ML systems
- Advanced proficiency in Python, with strong experience in at least one additional programming language (e.g., Java) and modern front-end technologies (e.g., React, TypeScript)
- Hands-on experience building and productionizing agentic AI systems, including multi-agent orchestration using frameworks such as LangChain, LangGraph, or equivalent
- Practical understanding of LLM orchestration, RAG, tool calling, prompt engineering, and dynamic reasoning
- Experience evaluating and integrating AI/LLM capabilities into production applications, including model evaluation, output quality monitoring, and feedback loops
- Hands-on experience with AI coding tools (Claude Code, Copilot, or similar) — you know when they accelerate work and when human judgment is critical
- Strong experience with cloud services such as AWS
Preferred qualifications, capabilities, and skills:
- Experience architecting solutions where AI tools handle implementation while you focus on business logic and edge cases
- Track record of rapid prototyping and iteration in ambiguous problem spaces, including UI experimentation based on user research and feedback
- Familiarity with vector databases (e.g., OpenSearch,FAISSDB) and embedding management