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Mid-level Hyderabad SDET/platform role with niche Kubernetes and AI skills yields moderate competition.
Specialized platform SDET skills transfer to cloud-native and observability teams but require domain-specific tooling knowledge.
Explicit 5–8 years plus mandatory SDET, Kubernetes, CI/CD, and AI platform skills make filtering strict.
Deploy and maintain lab environments for development, testing, and staging of the Skylar AI Platform to ensure monthly software update cadence.
Develop and maintain automated deployment pipelines with tests validating builds, staging, production parity, and performance gates including response time and throughput.
Own end-to-end testing workflows across multiple systems, including integration testing, regression prevention, rollback validation, telemetry generation, and documentation upkeep.
5-8 years of relevant work experience in platform engineering or SDET roles.
Proficiency in Node.js and/or Python focused on automation, with experience in API integration (REST/GraphQL).
Hands-on experience with Kubernetes, Docker, CI/CD pipeline automation tools (e.g., GitHub, GitOps), and automated test frameworks (e.g., Playwright).
Experience managing lab environments and maintaining software version synchronization across components.
Experience integrating AI platform components, including LLM API consumption and prompt engineering basics, to support AI-powered observability.
Strong cross-functional collaboration with product, data science, and engineering teams involving technical documentation and issue escalation.
Background in full-stack debugging, telemetry and observability tools (e.g., SkylarOne, Prometheus, Grafana), and ITSM workflows with ServiceNow.