Senior AI Platform Lead: Cloud, Data & ML

JP Morgan Chase; Plano (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorganChase in Plano, TX, seeks a Senior Lead Software Engineer within Corporate Technology – Chief Technology Office. You will be a senior technical leader, delivering trusted, scalable technology products and driving end-to-end delivery on agile teams.

You will lead architecture for ML workflows, build reusable APIs/SDKs, mentor engineers, and advance enterprise AI practices with production-grade validation and monitoring.

Qualifications

• 5+ years of software engineering experience in distributed systems.
• Strong Python, API/SDK design and code reviews.
• Experience with Generative AI platforms, LLM orchestration.
• AWS, Terraform, and containerization (EKS/ECS) expertise.
• Excellent communication with business and technical partners.

Responsibilities

• Lead hands-on technical delivery from design to production operations.
• Own architecture for ML workflows and data pipelines.
• Develop AI capabilities with production-ready monitoring and evaluation.
• Build reusable APIs/SDKs for platform adoption.
• Mentor engineers and contribute to engineering communities.
• Ensure platform reliability, scalability, and cost efficiency.
• Automate infrastructure provisioning and CI/CD pipelines.
• Drive adoption of enterprise AI practices and validation standards.
• Produce architecture artifacts aligned with enterprise standards.
• Collaborate with data scientists and product teams.
• Contribute to CTO office initiatives.

Skills

Python

APIs/SDKs

Architecture design

Mentoring

CI/CD

Agile delivery

Tools

Databricks

AWS

Terraform

EKS/ECS

GitHub Copilot

Claude Code

Job description

JPMorganChase in Plano, TX, seeks a Senior Lead Software Engineer within Corporate Technology – Chief Technology Office. You will be a senior technical leader, delivering trusted, scalable technology products and driving end-to-end delivery on agile teams.

You will lead architecture for ML workflows, build reusable APIs/SDKs, mentor engineers, and advance enterprise AI practices with production-grade validation and monitoring.