Lead Software Engineer, AI/ML, AI Agent Platform

JPMorgan Chase

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Work type
On-site
Location
Jersey City, NJPalo Alto, CASeattle, WAPlano, TXNew York, NY
Posted
2 days ago
Freshness
Confirmed live today

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Similar $188k
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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

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TL;DR · Lead Software Engineer, AI/ML, AI Agent Platform

As a Lead Software Engineer - AI/ML - AI Agent Platform within Enterprise Technology, AI and Machine Learning & Data Platforms, you will lead the technical design and delivery of an SDK and platform capabilities for large-language-model-powered agents. You will build core components including agent orchestration, tool calling, retrieval-augmented generation pipelines, and model-serving integrations. Your daily work involves developing voice agents with speech-to-text and text-to-speech capabilities, document-extraction systems using OCR, and agentic memory for context management. You will drive the improvement of NL2SQL and RAG through evaluation datasets and benchmarks while ensuring safety via guardrails and content filtering. Required skills include advanced Python proficiency, experience with LLM-enabled production systems, prompt engineering, and infrastructure like Docker, Kubernetes, and cloud platforms to solve complex problems in building reliable, scalable agentic AI experiences.

What you'll do

  • Lead the end-to-end delivery of the AI Agent Platform SDK and orchestration frameworks from design to production deployment.
  • Develop core platform building blocks including tool calling, retrieval-augmented generation (RAG), and model-serving integrations.
  • Build specialized agent modalities for voice interaction, document extraction, and long-term agentic memory systems.
  • Improve capabilities like NL2SQL and RAG by creating evaluation datasets, benchmarks, and iterative prompt engineering.
  • Establish engineering standards for reliability, latency, and developer experience through system design and code reviews.
  • Build and operate observability tools including tracing, cost telemetry, and automated regression suites.
  • Implement enterprise safety and governance patterns such as guardrails, content filtering, and prompt-injection defenses.
  • Collaborate with stakeholders to define product roadmaps, success metrics, and high-impact technical priorities.

What we're looking for

  • Formal training or certification in applied artificial intelligence and machine learning concepts.
  • 5+ years of experience in applied artificial intelligence and machine learning.
  • Advanced proficiency in Python with strong software engineering fundamentals including testing, design patterns, and version control.
  • Experience building, evaluating, and deploying ML or LLM-enabled systems into production as reusable libraries, SDKs, or platform services.
  • Practical experience with prompt engineering and RAG, including building evaluation methods and benchmarks to improve capabilities like NL2SQL.
  • Experience designing and operating reliable, data-intensive services with incident response readiness and performance tuning.
  • Demonstrated ability to lead technical decisions through ambiguity and communicate trade-offs to both technical and non-technical stakeholders.
  • Experience with agent orchestration frameworks, voice agents, document extraction, agentic memory, vector databases, CI/CD, or cloud platforms (preferred).

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