Description

You design and build tools and services to validate the reliability, performance, and correctness of ML data pipelines and AI infrastructure.

This role is on-site.

Responsibilities

• Develop platform-level test solutions and automation frameworks using Python, Terraform, and cloud-native practices.
• Integrate automated testing, resilience checks, and observability hooks into the CI/CD pipeline.
• Lead initiatives driving testability, platform resilience, and validation as code across the ML platform stack.
• Collaborate with engineering, MLOps, and infrastructure teams to embed quality engineering into platform components.
• Build reusable components supporting scalability, modularity, and self-service quality tooling.

Required Skills

• 8+ years of hands-on software development experience, including large-scale backend or platform engineering.
• Expert in Python, including object-oriented programming, testing frameworks, and automation libraries.
• Proficient in Infrastructure as Code using Terraform to manage cloud infrastructure.
• Experience building or validating platform infrastructure with CI/CD systems (GitHub Actions, Jenkins).
• Solid experience with AWS services (Lambda, S3, ECS/EKS, Step Functions, CloudWatch).
• Strong understanding of software engineering best practices: code quality, reliability, performance optimization, and observability.

Key Skills

Education

Any Graduate