Principal Software Engineer, AI Foundations

JPMorgan Chase

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 58 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $201k

$127k most similar roles pay here $291k

This listing doesn't post a salary. Most similar roles pay $174,600–$228,062.

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 · Principal Software Engineer, AI Foundations

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As a Principal Software Engineer - AI Foundations within the Chief Data and Analytics Office, you will join an agile team to build and deliver secure, scalable, and high-quality AI-enabled applications and services. Your daily responsibilities include developing production code, managing SDK and service integrations, and designing end-to-end MLOps capabilities such as data versioning, reproducible training pipelines, and CI/CD for models. You will also contribute to next-generation training techniques like distributed fine-tuning and synthetic data generation while architecting agentic AI-enabled engineering workflows. The role requires expert proficiency in Python, Java, Scala, or Go, along with cloud-native experience in containers and orchestration. You will solve complex problems in platform engineering, ML systems, and distributed systems to create reusable frameworks and durable components that improve delivery speed and operational performance across the firm's portfolios.

What does a Software Engineer earn?

Median $197500 from 2196 postings across 133 companies.

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Skills

Python Java Scala Go MLOps LLM AI CI/CD Distributed Systems Ray REST Data Engineering System Design Cloud-native RLHF DPO

What you'll do

Design, build, and troubleshoot scalable AI-enabled applications and services.
Develop high-quality production code while reviewing and debugging code from other team members.
Implement end-to-end MLOps capabilities including data versioning, training pipelines, and CI/CD for models.
Contribute to advanced training techniques like distributed fine-tuning, RLHF, and synthetic data generation.
Architect and govern agentic AI-enabled engineering workflows to improve delivery speed and code quality.
Create durable, reusable frameworks and platform components for use across multiple teams.
Automate the remediation of recurring issues to improve the reliability and performance of AI features.
Influence senior stakeholders to align technical roadmaps with business outcomes and safety standards.

What we're looking for

Formal training or certification in software engineering concepts and at least 7 years of applied experience.
Expert proficiency in one or more programming languages such as Python, Java, Scala, or Go.
Experience designing and leading the adoption of agentic AI-enabled development practices across teams.
Proven ability to design and operate ML/LLM platforms including training pipelines, experiment tracking, and model versioning.
Practical experience with cloud-native technologies including containers, orchestration, infrastructure as code, and observability.
Strong understanding of responsible AI use, security, and risk-based governance in engineering workflows.
Experience solving complex problems across platform engineering, ML systems, data engineering, or distributed systems.
Ability to communicate technical topics effectively to influence senior leaders and executives regarding business outcomes.

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