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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand and metro Hyderabad location increase applicant density despite seniority and specialized DevOps focus.
Deep platform DevOps, Kubernetes, observability, and AI-native tooling needs make cross-industry mobility moderately transferable.
Explicit 12+ years plus staff-level requirement and mandatory Kubernetes, CI/CD, and observability skills produce high shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and execution of CI/CD pipeline enablement and developer productivity improvements across DevOps functions.
Own and develop cross-team AI-native development platform components including Application Rating Tool, Pod Coach agent, and IT triage agent with AI automation.
Drive shift-left performance engineering strategy, integrating performance monitoring and tooling early in development lifecycle and collaborating on MCP integration.
Minimum Requirements
12+ years of software engineering experience in high-traffic, cloud-based environments with at least 3 years in senior or staff-level individual contributor roles.
Strong proficiency in Java, JavaScript, and/or Python; comprehensive knowledge of distributed systems and scalable service design.
Expert-level experience with CI/CD platforms (e.g., Jenkins, GitHub Actions), Kubernetes, container orchestration, and observability tools (Grafana, Prometheus, OpenTelemetry).
Demonstrated experience integrating AI/ML or agentic AI into engineering workflows; experience with platforms like MCP or A2A is a plus but not mandatory.
Ideal Candidate Profile
Experienced technical leader skilled in cross-functional collaboration with product, engineering, and UX teams to drive platform engineering initiatives with business impact.
Proven ability to architect and implement scalable DevOps and AI-native tooling solutions supporting developer productivity and operational excellence.
Depth in performance engineering with hands-on expertise in shift-left strategies, monitoring, and incident response within Kubernetes-based cloud environments.