- Location
- Bengaluru, KA,IN, IN
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Experience
- 8+ years
- Source
- Eightfold
Description
Design and build scalable test automation frameworks, shared services, libraries, and developer tools. Create reusable capabilities for browser, API, integration, contract, performance, accessibility, and end-to-end testing. Establish engineering standards for automation architecture, code quality, testability, reliability, and maintainability. Integrate automated quality checks, release validations, and quality gates into CI/CD pipelines. Improve test execution speed, parallelization, diagnostics, stability, and feedback time. Build observability into automation platforms using logs, metrics, traces, dashboards, and alerts. Correlate test results with build, deployment, application, and production telemetry. Partner with development, DevOps, SRE, security, architecture, and release teams to improve delivery quality. Mentor engineers and manual testers in software development, automation, DevOps, and AI-assisted engineering. Reduce duplicated frameworks and promote common platforms and reusable engineering patterns. 8+ years of experience in software engineering, quality engineering, DevOps, SRE, platform engineering, or test architecture. Strong programming skills in TypeScript, JavaScript, Python, Java, C#, or a comparable language. Experience designing maintainable automation frameworks or internal engineering platforms. Hands-on experience with Playwright, Selenium WebDriver, or similar browser automation technologies. Strong experience with API, integration, contract, and end-to-end testing. Experience with Azure DevOps, GitHub Actions, Jenkins, or another CI/CD platform. Practical knowledge of Git, pull requests, code reviews, build systems, and deployment workflows. Experience with Docker, Kubernetes, cloud services, and modern application architectures. Knowledge of observability, including logging, metrics, tracing, dashboards, and failure diagnostics. Hands-on experience using Claude Code/Codex or comparable AI coding assistants for substantive engineering work. Practical understanding of MCP, tool calling, and agentic application development. Ability to evaluate and govern AI-generated code and autonomous workflows. Experience building shared engineering platforms or developer-productivity tools. Experience with OpenTelemetry, Azure Monitor, Application Insights, Datadog, Grafana, or Splunk. Knowledge of performance, security, accessibility, resiliency, and production validation. Experience with retrieval-augmented generation, vector search, AI evaluation, or multi-agent systems. Experience modernizing teams that rely heavily on manual testing or tool-specific automation. What Success Looks Like Product teams adopt common engineering capabilities instead of creating separate automation frameworks. CI/CD feedback becomes faster, more reliable, and more actionable. Test flakiness, duplicated effort, and automation maintenance costs are reduced. AI-assisted development produces measurable improvements in engineering productivity and defect detection. Agentic solutions operate with appropriate security, evaluation, governance, and human oversight. Manual testers develop stronger programming, automation, DevOps, and AI-engineering skills. The strongest candidate will think like a software engineer and platform builder who specializes in quality. They should be able to demonstrate systems they have designed and built—not only tools they have used.
