Lead Software Engineer - AI/ML Data Platform (Test Engineering)

Job Description

At J.P.

Morgan Chase, we are building an enterprise-grade AI/ML Data Platform that enables scalable, secure, and responsible machine learning across the firm.

We are seeking a Lead Software Engineer with a strong background in software development and platform engineering to help drive the Test Engineering Program-a strategic initiative focused on building robust, intelligent validation frameworks and infrastructure that power our ML and data products.
This is a software engineering role embedded in quality and reliability initiatives.

You'll architect and develop tools, services, and automation that elevate platform assurance across large-scale distributed systems.

If you're passionate about platform quality, CI/CD excellence, infrastructure-as-code, and bringing engineering rigor to validation, this is your opportunity to make a major impact.

Key Responsibilities

• Design and build high-performance tools and services to validate the reliability, performance, and correctness of ML data pipelines and AI infrastructure.
• Develop platform-level test solutions and automation frameworks using Python, Terraform, and modern cloud-native practices.
• Contribute to the platform's CI/CD pipeline by integrating automated testing, resilience checks, and observability hooks at every stage.
• Lead initiatives that drive testability, platform resilience, and validation as code across all layers of the ML platform stack.
• Collaborate with engineering, MLOps, and infrastructure teams to embed quality engineering deeply into platform components.
• Build reusable components that support scalability, modularity, and self-service quality tooling.
• Mentor junior engineers and influence technical standards across the Test Engineering Program.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 5+ years of hands-on software development experience, including large-scale backend systems or platform engineering.
• Expert in Python with a strong understanding of object-oriented programming, testing frameworks, and automation libraries.
• Experience building or validating platform infrastructure, with hands-on knowledge of CI/CD systems, GitHub Actions, Jenkins, or similar tools.
• Solid experience with AWS services (Lambda, S3, ECS/EKS, Step Functions, CloudWatch).
• Proficient in Infrastructure as Code using Terraform to manage and provision cloud infrastructure.
• Strong understanding of software engineering best practices: code quality, reliability, performance optimization, and observability.

Preferred Qualifications

• Exposure to machine learning workflows, model lifecycle management, or data engineering platforms.
• Experience with distributed systems, event-driven architectures (e.g., Kafka), and big data platforms (e.g., Spark, Databricks).
• Familiarity with banking or financial domain use cases, including data governance and complia...