Lead Software Engineer

JPMorgan Chase

Confirmed live 2 days ago Trusted

Quick summary

Work type
On-site
Location
Wilmington, DE
Posted
17 days ago
Freshness
Confirmed live 2 days ago

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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 $184,425–$211,200.

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 · Lead Software Engineer

As a Lead Software Engineer within the Corporate - AIML Data Platforms team, you will serve as a technical leader designing, building, and operating foundational cloud infrastructure for data scientists and machine learning engineers. You will develop reusable AI/ML platform infrastructure, manage GPU-intensive workloads, and implement infrastructure-as-code solutions to streamline model deployment and environment provisioning. Your daily work involves creating production-grade services, APIs, and SDK integrations while optimizing for reliability, scalability, and cost through orchestration and hardware acceleration. The role requires expertise in Python, Java, or Go, along with proficiency in AWS, Docker, Kubernetes, and Terraform. You will manage the AI/ML lifecycle using tools like Kubeflow and MLflow while integrating frameworks such as PyTorch and TensorFlow to solve complex infrastructure challenges and support enterprise LLM operationalization within a distributed systems environment.

What you'll do

  • Build and maintain reusable AI/ML platform infrastructure and shared services for large-scale deployment.
  • Architect and operate secure, container-based cloud environments for training and inference including GPU workloads.
  • Implement infrastructure-as-code solutions to automate model deployment, environment provisioning, and release management.
  • Develop production-grade APIs, SDKs, and workflows to support the AI application lifecycle.
  • Optimize platform reliability, scalability, latency, and cost through orchestration and hardware acceleration.
  • Establish operational best practices for monitoring, logging, observability, and incident response.
  • Operationalize enterprise LLMs including fine-tuning workflows and inference strategies.
  • Lead the adoption of AI-assisted engineering practices to improve code quality and delivery speed.

What we're looking for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Experience delivering secure, production-quality code in Python or Java.
  • Strong foundations in distributed systems, microservices, and platform architecture/design principles.
  • Proven ability to architect and operate cloud-native infrastructure on AWS and other major clouds.
  • Demonstrated expertise with infrastructure-as-code tooling, specifically Terraform, in large-scale environments.
  • Hands-on experience with Docker and Kubernetes, including AWS EKS operations.
  • Experience building or supporting production AI/ML platforms, including GPU infrastructure and model serving.
  • Strong DevOps practices including CI/CD, release automation, automated testing, and observability.
  • Experience with SQL/NoSQL databases, Linux, scripting, and networking fundamentals.
  • Demonstrated experience leading the use of approved AI-assisted software development tools and coaching others on safe adoption.
  • Proficiency in Go or Python for automation and tooling (preferred).
  • Experience with MLOps frameworks like Kubeflow or MLflow (preferred).
  • Working knowledge of ML frameworks such as PyTorch, TensorFlow, or Hugging Face (preferred).
  • Exposure to multi-cloud or hybrid cloud architectures (preferred).

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