AI Data Platform Reliability & Validation Engineer

Responsibilities

• Design, develop, and execute end-to-end (E2E) scenario validations that simulate real-world usage of complex AI data platform workflows (data ingestion, transformation, ML pipeline orchestration, etc.).
• Collaborate closely with product, engineering, and field teams to identify gaps in coverage and propose test automation strategies.
• Develop and maintain automated test frameworks supporting E2E, integration, performance, and regression testing for distributed data / AI services
• Monitor system health across the stack (infrastructure, data pipelines, AI / ML workloads), proactively detect failures or SLA breaches.
• Champion SRE best practices including observability, incident management, blameless postmortems, and runbook automation.
• Analyze logs, traces, and metrics to identify reliability, latency, and scalability issues; drive root cause analysis and corrective actions.
• Partner with engineering to drive high-availability, fault tolerance, and continuous delivery (CI / CD) improvements.
• Participate in on-call rotation to support critical services, ensuring rapid resolution and minimizing customer impact.

Desired Qualifications :