Lead Software Engineer, Applied AI ML Lead

JPMorgan Chase

Confirmed live 2 days ago Low trust

Quick summary

Work type
On-site
Location
Palo Alto, CA
Posted
52 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $211k
$179k most similar roles pay here $236k

This listing doesn't post a salary. Most similar roles pay $192,050–$230,400.

Based on 240 similar postings.

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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.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Applied AI ML Lead

As a Lead Software Engineer - Applied AI ML Lead within the Enterprise Technology Infrastructure Platforms team, you will serve as a core technical contributor in an agile environment. You will design, develop, and productionize GenAI and agentic AI solutions, including RAG systems, while driving the adoption of AI-assisted engineering practices to improve code quality and delivery speed. Your daily work involves building backend services, managing data ingestion pipelines, and implementing MLOps best practices for lifecycle management. You will utilize Python, Java, Apache Spark, Apache Airflow, and Apache Iceberg to solve complex problems in infrastructure capacity optimization and operational automation. The role focuses on creating scalable, secure, and stable technology products by developing prompt engineering assets, establishing guardrails, and managing the end-to-end AI strategy to ensure high performance across various business functions.

What you'll do

  • Design and productionize GenAI/agentic AI solutions including RAG, summarization, and extraction for automation and decision support.
  • Develop production-grade backend services using Python or Java to build REST APIs, microservices, and data ingestion pipelines.
  • Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
  • Build prompt engineering assets, routing strategies, and guardrails while implementing automated and human-in-the-loop evaluations.
  • Implement MLOps best practices for model experimentation, versioning, CI/CD, deployment, monitoring, and lifecycle management.
  • Own infrastructure capacity optimization by building predictive models to identify performance bottlenecks and right-sizing opportunities.
  • Manage the end-to-end AI/ML optimization strategy including architecture standards, security, and cross-functional execution.
  • Lead technical evaluations with external vendors and internal teams to assess architectural designs and system applicability.

What we're looking for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Hands-on practical experience in system design, application development, testing, and operational stability.
  • Advanced proficiency in one or more programming languages.
  • Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring security and performance.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling.
  • Proficiency in all aspects of the Software Development Life Cycle.
  • Strong hands-on experience with Apache Spark, Apache Airflow, and Apache Iceberg.
  • Proven delivery of AI/ML and GenAI solutions (RAG, extraction, summarization) and deep expertise in distributed systems and production engineering.
  • Experience with MCP, Agent Skills, and structured agentic architectures (preferred).
  • Strong practical usage of AI engineering productivity tooling like GitHub Copilot or Claude Code (preferred).
  • Familiarity with VSI and Cloud Foundry contexts (preferred).
  • Advanced Java engineering proficiency in addition to Python (preferred).

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