Lead Software Engineer - Agentic AI
JPMorgan Chase6 hours ago
Responsibilities
- Execute software design, development, and technical troubleshooting 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 SDKs, reference implementations, and integration patterns.
- Build scalable agent interfaces and backend services with retrieval, orchestration, tool-calling, and memory capabilities.
- Establish quality, performance, monitoring, testing, operational, and incident-readiness standards for agent workloads.
- Drive architecture decisions, scalable designs, and repeatable deployment practices to move experimentation into production.
- Embed governance, privacy, model-risk, security, and responsible AI considerations into platform design.
- Partner with product, engineering, risk, and control stakeholders to align requirements and trade-offs.
- Communicate technical strategy and progress to senior stakeholders.
- Lead adoption of enterprise-authorized AI-assisted engineering tools and establish standards for validating AI-generated outputs.
Requirements
- Formal training or certification in software engineering concepts and 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 and RAG 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, or Server-Sent Events.
- Experience leading effective use of approved AI-assisted software development tools for coding, review, testing, troubleshooting, and related workflows.
- Strong understanding of responsible AI engineering, data sensitivity, secure input/output handling, resiliency, security, and compliant adoption practices.
- Production experience with multi-agent and workflow orchestration frameworks such as LangGraph, AutoGen, CrewAI, LlamaIndex Workflows, or Semantic Kernel.
- Deep expertise in model and function tool calling, JSON schema validation, dynamic API integration, sandboxed code execution, and MCP.
- Experience implementing short-term and episodic memory using scratchpads, state graphs, vector retrieval, and conversational buffer compaction.
- Advanced knowledge of prompt engineering, chain-of-thought, ReAct, reflection loops, output grounding, and guardrails such as NeMo Guardrails or Guardrails AI.
- Preferred experience building agent systems, orchestration patterns, development tooling, or evaluation frameworks.
- Preferred experience designing scalable inference or model-serving architectures and optimizing latency, throughput, and cost.
- Preferred familiarity with responsible AI, model risk, governance-by-design, open-source machine learning or infrastructure ecosystems, and regulated financial services use cases.
Benefits
- Competitive total rewards package with eligibility-based benefits and possible commission or discretionary incentive compensation.
- Comprehensive health care coverage.
- On-site health and wellness centers.
- Retirement savings plan.
- Backup childcare.
- Tuition reimbursement.
- Mental health support.
- Financial coaching.
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.