Platform Engineer- Automation, Kubernetes- Skylar AI Platform
ScienceLogic (company site, opens in a new tab)5–8 yrsHyderabadHybridDirect career pageEst. 12–22 LPA
Posted on 10 Sept
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Job description
Structured overview of role & requirements
About This Role
- Deploy and maintain lab environments supporting multiple types for development, testing, and staging of the Skylar AI platform.
- Manage automated deployment pipelines with continuous integration testing to ensure staging matches production and validate system performance metrics like response times and resource consumption.
- Lead end-to-end platform testing including integration, regression, rollback validation, and user journey simulation to prevent breaks and ensure system reliability.
Minimum Requirements
- 5-8 years of relevant work experience in platform engineering or similar roles.
- Proficiency in Node.js and/or Python focusing on automation development, and familiarity with REST/GraphQL APIs.
- Solid experience with Docker, Kubernetes, CI/CD pipelines (e.g., GitHub, GitOps), and test automation frameworks (such as Playwright).
- Not explicitly mentioned in the JD: degree requirements, explicit onsite/location constraints, or notice period.
Ideal Candidate Profile
- Experienced in developing and maintaining complex AI-powered observability platforms with a focus on automation and testing.
- Comfortable working cross-functionally across product management, engineering, and data science teams to enable platform usage and issue resolution.
- Skillful in integrating telemetry, event logging, service management tools (ServiceNow), and applying AI platform knowledge such as LLM API consumption and prompt engineering.