Member of Technical Staff

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry.

This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.

Join the Pipeline Engineering team at Everpure™ as a Software Engineer to build, own, and operationally scale the microservices and Temporal workflows driving continuous integration for FlashArray, FlashBlade, and Hyperscale. In this developer-first role based in Bangalore, you will design durable production services and agentic AI tools that directly reduce time-to-signal, optimize compute utilization, and absorb operational toil across our global engineering workforce.

• Architect Deterministic CI Workflows: Design and deploy production microservices and durable Temporal workflows that make pipeline execution resilient, resumable, and fully debuggable for enterprise storage platforms.

• Optimize Compute & Testbed Utilization: Extend in-house scheduling logic and placement algorithms across bare-metal hardware and VM fleets to minimize queue times and maximize infrastructure efficiency.

• Build Operational AI Agents: Engineer RAG pipelines and agentic workflows over failure logs, vector stores, and test metadata to automate root-cause analysis, flake classification, and developer triage.

• Drive Platform Observability & Ownership: Establish key platform metrics—including time-to-signal and pass/flake rates—while operating your services end-to-end to ensure long-term stability and eliminate recurring failure modes.

• Collaborate Across Product Teams: Partner with platform and product engineering groups to deliver developer experience improvements, self-service tools, and streamlined integration paths.

WHAT YOU BRING

• Backend & Systems Engineering: Strong expertise in typed systems languages (such as Go or Rust) for backend platform services, paired with Python proficiency for automation and AI logic integration.

• Distributed Systems & Operational Fundamentals: Practical mastery of microservice architecture (concurrency, retries, idempotency) along with solid Linux/Unix debugging skills across network, storage, and application layers.

• AI & Retrieval Integration: Practical knowledge of building agentic workflows, prompt design, and integrating LLM APIs with vector databases and