Lead Software Engineer - Agentic AI
JPMorgan Chase6 hours ago
Responsibilities
- Execute software design, development, troubleshooting, and critical technology solutions across multiple technical areas.
- Define and drive the platform roadmap for agent-based capabilities with measurable outcomes, reliability, and usability.
- Lead end-to-end delivery of agent platform components, including software development kits, reference implementations, and integration patterns.
- Build scalable agent interfaces, backend services, hybrid search and RAG pipelines, orchestration workflows, memory systems, and tool-calling integrations.
- Establish quality, performance, monitoring, testing, operational, and incident-readiness standards for agent workloads.
- Drive architecture decisions, scalable designs, and repeatable deployment practices for production systems.
- Embed governance, privacy, responsible AI, and model risk considerations into platform design.
- Partner with product, engineering, risk, and control stakeholders and communicate technical strategy to senior stakeholders.
- Promote enterprise-authorized AI-assisted engineering practices, validation standards, secure coding, peer review, automated testing, and reuse of effective patterns.
Requirements
- Formal training or certification in software engineering concepts and at least 5 years of applied experience.
- Proficiency in Python and/or TypeScript, Java, or Go for agent orchestration and enterprise backend integration.
- Experience designing hybrid search pipelines using dense vector retrieval, BM25, rerankers, and vector databases.
- Experience building scalable microservices and agent interfaces with FastAPI, Spring Boot, or Node.js, including REST, WebSockets, and Server-Sent Events.
- Experience leading approved AI-assisted software development practices for coding, code review, testing, and troubleshooting, including validation of AI outputs for correctness, performance, and security.
- Understanding of responsible AI use, data sensitivity, secure input and output handling, resiliency, security, and compliant engineering practices.
- Production experience with multi-agent and workflow orchestration frameworks such as LangGraph, AutoGen, CrewAI, LlamaIndex Workflows, or Semantic Kernel.
- Expertise in model tool calling, JSON schema validation, dynamic API integration, sandboxed code execution, and MCP.
- Experience implementing short-term and episodic memory, state graphs, vector retrieval, conversational buffers, and memory compaction.
- Advanced knowledge of prompt engineering, chain-of-thought, ReAct, reflection loops, output grounding, and guardrails.
- Preferred experience with agent-based systems, orchestration patterns, agent tooling, evaluation frameworks, scalable inference or model serving, responsible AI, model risk, open-source machine learning or infrastructure software, and regulated financial services use cases.
Benefits
- Competitive total rewards and benefits package, with eligible roles potentially receiving commission-based pay or discretionary incentive compensation in cash and/or forfeitable equity.
- Benefits may include comprehensive health care, on-site health and wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Additional compensation and benefits details are provided during the hiring process.
Tech Stack
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.