Jobs / JPM***
Executive Director Principal Software Engineer - Agentic Engineering
JPM*** · Jersey City, NJ, United States
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Jersey City, NJ, United States204,250-285,000 USD/yearlyRemote
Remuneration
204,250-285,000 USD/yearly
Location
Jersey City, NJ, United States
Visa sponsorship
Sponsors visa
Job summary
JOB DESCRIPTION If you are looking for a game-changing career, working for one of the world's leading financial institutions, you've come to the right place. As the Principal Software Engineer at JPMorgan Chase within the Corporate and Investment Bank Technology – Securitized Product Group Technology team, you will lead the design, build, and scaling of our next-generation multi-agent AI platform.
Benefits
And programs to meet employee needs, based on eligibility.Additional details about total compensation andWill be provided during the hiring process.We recognize that our people are our strength and the diverse talents they bringWe are an equal opportunity employer and place a high value on diversity and incVisit our FAQs for more information about requesting an accommodation.JPMorgan Chase & Co.Is an Equal Opportunity Employer, including Disability/VeteransABOUT THE TEAMMorgan's Commercial & Investment Bank is a global leader across banking, marketsCorporations, governments and institutions throughout the world entrust us withThe Commercial & Investment Bank provides strategic advice, raises capital, mana
Qualifications
- If you are looking for a game-changing career, working for one of the world's leading financial institutions, you've come to the right place.
- capabilities, and
Responsibilities
- Own the multi-year agentic platform strategy: agent toolchains, RAG pipelines, memory/state architectures, context management, evaluation, and feedback/reinforcement loops.
- Architect scalable multi-agent systems using LangChain, LangGraph, AutoGen, or equivalent frameworks—and define when to use simpler primitives.
- Design distributed ingestion and workflow systems (batch + streaming) with data contracts, lineage, and strong data-quality patterns.
- Establish standards for the agentic development lifecycle: context engineering, automated evals, observability, security, and release readiness.
- Contribute directly in Python (services, concurrency, performance, reliability) and set the bar via reference implementations.
- Lead design and code reviews; engage directly in incident response and production hardening.
- Build reusable agent components: planning/decomposition, tool/function calling, self-critique/reflection loops, state management, multi-agent coordination, and safety controls.
- Partner with MLOps/platform on deployment, monitoring, and retraining pipelines (MLflow, SageMaker, Vertex AI, Azure ML, etc.).
- Required
Skills
Communication
Degrees
Associate
Work schedule
On-call
Industry
AutomotiveBankingGamingHealthcareMediaPublic-sector
Company size
Smb
Contract length
00 years