Lead Software Engineer, AI Engineer

JPMorgan Chase

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: Plano, TX
Posted: 46 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $198k

$174k most similar roles pay here $231k

This listing doesn't post a salary. Most similar roles pay $184,900–$211,200.

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, AI Engineer

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Lead Software Engineer - Ai Engineer joins the Automation & AI Solutions team within the Commercial & Investment Bank to architect, design, and deliver scalable software products. This role focuses on building cloud-native microservices and integrating generative AI and LLM capabilities into business workflows. The engineer will lead the creation of AI-driven services, manage orchestration, and drive the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed. Key responsibilities include developing RESTful APIs, automating operational solutions for system stability, and ensuring secure production-ready deployments. Technical requirements include proficiency in Java, Python, AWS ECS, EKS, and Postgres, along with experience in PyTorch, TensorFlow, scikit-learn, and Hugging Face. The role addresses the challenge of implementing responsible AI, RAG, and agentic workflows within a secure, high-scale distributed systems environment.

Skills

Java Python AWS Kubernetes Docker LLM Generative AI PyTorch TensorFlow scikit-learn Hugging Face REST Microservices CI/CD Helm RAG Agile Scrum

What you'll do

Architect and deliver scalable cloud-native microservices and APIs using Java, AWS, and Postgres.
Design and implement LLM-based services, including RAG, agent orchestration, and integration into business workflows.
Lead the adoption of enterprise-authorized AI tools to improve code quality, testing, and development speed.
Validate all AI-generated outputs for security, performance, and accuracy through peer reviews and automated testing.
Automate solutions for recurring operational issues to improve system stability and observability.
Influence product design and technical architecture by proposing pragmatic trade-offs aligned with firm security standards.
Guide the team on responsible AI practices, including data sensitivity and secure handling of inputs/outputs.

What we're looking for

Formal training or certification in Software Engineering and 5+ years of applied experience.
Experience with Large Language Models, generative AI use cases, and AI/ML frameworks like PyTorch, TensorFlow, or Hugging Face.
Hands-on experience using enterprise-authorized AI-assisted software development tools to improve code quality, testing, and documentation.
Expertise in microservices, RESTful APIs, and data technologies including relational and NoSQL databases.
Experience with distributed systems and at least one major cloud platform (AWS, GCP, or Azure).
Practical experience building cloud-native systems using event-driven architectures, streaming, and service mesh.
Advanced Java proficiency (preferred) and working knowledge of Python for AI/ML integrations (preferred).
Cloud certification in AWS, GCP, or Azure (preferred).