Lead Software Engineer and ML Engineer - Sales Copilot

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 JPMorganChase within the Commercial and Investment bank Digital & Platform Services, Data Analytics, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.

As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

JPMorganChase is hiring top talent to join the growing Commercial & Investment Bank Technology organization within Digital & Platform Services / Data Analytics, building production AI agents on NEO that leverage the firm's scale, data, and full-service advantage to deliver measurable impact across the Commercial & Investment Bank and Payments.

As a Senior AI Application Engineer, you'll design, productionize, and operate LLM-powered agents on NEO (the firm's agent runtime PaaS on AWS/Azure), partnering closely with business, product, and engineering teams in a fast-paced environment.

Job responsibilities


* Design and ship production agents on NEO across the federated portfolio, owning them from prototype through production.


* Build retrieval that holds up in production: Graph RAG combining knowledge-graph traversal with vector search, plus chunking, ranking, and grounding strategies that keep answers accurate and auditable.


* Design agent memory: episodic and semantic memory organized as memory nodes, with recall, summarization, and decay policies tuned per use case.


* Own organizational context management - assembling entitlement-, lineage-, and tenant-aware context so each agent reasons over only what it's allowed to see.


* Compose multi-agent workflows using A2A, and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk).


* Build and run evals: task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, and quality/safety gating before release.


* Deploy and operate solutions on public cloud (AWS and, or Azure) with strong SDLC, security, resiliency, and observability practices.


* Partner with product and business partners across CIB and Payments to turn use cases into shipped, supported agents.


* Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts and 5+ years applied experience with at least 4 years working on AI/ML solutions.


* Hands-on practical experience delivering system design, applica...