Principal Software Engineer, AI Engineer

JPMorgan Chase

Confirmed live 2 days ago Trusted

Quick summary

Work type
On-site
Location
Jersey City, NJ
Posted
78 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $203k
$127k most similar roles pay here $291k

This listing doesn't post a salary. Most similar roles pay $174,600–$230,625.

Based on 240 similar postings.

Employer

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 · Principal Software Engineer, AI Engineer

As a Principal Software Engineer - AI Engineer within the Corporate Sector – AI/ML & Data Platforms for LLM Suite team, you will lead a specialized technical area and mentor a team of machine learning and software engineers. You will be responsible for designing and implementing agentic AI reference architectures, including orchestration, retrieval, memory, guardrails, and evaluation harnesses. Your daily work involves writing production-quality Python code using PyTorch or TensorFlow, building LLM-powered APIs and microservices, and managing the end-to-end ML lifecycle including CI/CD, monitoring, and drift detection. You will utilize vector storage systems, cloud-native environments like AWS or Azure, and advanced MLOps practices to optimize inference for latency and cost. The role focuses on developing agentic AI systems and engineering workflows within a regulated environment to improve delivery speed and operational outcomes at scale.

What you'll do

  • Design and implement agentic AI reference architectures including orchestration, retrieval, memory, and evaluation harnesses.
  • Write production-quality Python code using PyTorch or TensorFlow and perform critical-path code reviews.
  • Build and operate LLM-powered APIs and microservices integrated into internal and client workflows.
  • Manage the end-to-end ML lifecycle including CI/CD, monitoring, drift detection, and model versioning.
  • Optimize inference for latency, throughput, caching, batching, and cost per inference.
  • Partner with data teams to develop structured and unstructured data pipelines and document ingestion systems.
  • Establish engineering standards for agentic AI systems and lead technical design reviews.
  • Architect and govern AI-enabled engineering workflows to improve delivery speed and code quality at scale.

What we're looking for

  • Formal training or certification in software engineering concepts and at least 7 years of applied experience.
  • Strong Python engineering skills with experience using PyTorch or TensorFlow.
  • Expertise in vector storage systems and designing memory for AI agents.
  • Experience developing long-running autonomous agents that utilize tools, skills, and human-in-the-loop components.
  • Proven experience deploying LLM-backed services to production as APIs and microservices.
  • Deep MLOps experience including CI/CD, monitoring, incident response, and model governance.
  • Cloud-native AI deployment experience on AWS or Azure with a focus on cost and performance optimization.
  • Experience designing and leading the adoption of agentic AI-enabled development practices across teams.

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