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Popular platform role title, mid-level experience band, and broad AI-plus-platform skillset increase applicant competition.
Platform and AI-tooling skills are moderately transferable but require specific platform and AI orchestration experience.
Explicit 2-4 year requirement plus mandatory AI-tooling, cloud, Kubernetes, and specific tooling skills raises filtering strictness.
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Develop and maintain AI-powered internal platform tools that enable engineers to perform functional and non-functional testing efficiently.
Research and design platform features optimized for large language models to assist engineering test planning and execution.
Mentor engineers and drive adoption of AI-assisted tooling within the engineering organization.
2-4 years of experience as a platform, performance, or software engineer building internal tools.
Proven experience using AI developer tools like Claude Code or Cursor for coding and debugging.
Strong background in large-scale, distributed cloud systems and microservice architectures; familiarity with CI/CD tools such as Docker and Kubernetes.
Work Experience Required: 2-4 years; Notice Period: Not explicitly mentioned in the JD.
Demonstrated ability to independently research and build AI-first tooling strategies integrating large language models effectively.
Experience delivering measurable impact through AI-driven tooling to detect and mitigate functional and performance bottlenecks.
Able to mentor peers and advocate AI tooling adoption, contributing to a culture of learning and continuous engineering improvements.