Description

Architect and develop validation frameworks for an AI/ML Data Platform to ensure reliability and correctness.

This role is on-site.

Responsibilities

• Design and build high-performance tools to validate ML data pipelines and AI infrastructure.
• Develop platform-level test solutions and automation frameworks using Python and cloud-native practices.
• Integrate automated testing, resilience checks, and observability hooks into CI/CD pipelines.
• Lead initiatives to drive testability and validation as code across the ML platform stack.
• Collaborate with engineering and MLOps teams to embed quality engineering into platform components.

Required Skills

• 8+ years of hands-on software development experience, including large-scale backend systems.
• Expert proficiency in Python with strong object-oriented programming skills.
• Proficient in Infrastructure as Code using Terraform for cloud infrastructure management.
• Strong experience with AWS services, including Lambda, S3, ECS/EKS, Step Functions, and CloudWatch.
• Experience building or validating platform infrastructure using CI/CD systems like GitHub Actions or Jenkins.
• Deep understanding of software engineering best practices, code quality, and observability.
• Proven track record developing large-scale distributed systems.

Preferred Skills

• Experience with AI/ML data platform architectures.

Key Skills

Education

Any Graduate