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Fullstack Software Engineer

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Onsite

Fullstack Software Engineer

Pure Storage

Fullstack Software Engineer

Skills

PythonGolangMicroservicesMachine LearningAI

2 months ago

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Important information


Salary:

$180,000 – $326,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

4 September 2026

What they need


Who you are

  • Full-Stack Engineering Capability: Demonstrated expertise in architecting, building, and maintaining production-grade backend microservices and modern frontend applications using Go and Python
  • GenAI & RAG Platform Expertise: Hands-on experience building Retrieval-Augmented Generation (RAG), LLM pipelines, or AI/ML-driven architectures to solve complex data processing and retrieval challenges
  • Autonomous Problem-Solving & Initiative: Strong ability to independently define technical approaches, evaluate complex trade-offs, and collaborate cross-functionally to bring innovative concepts to launch
  • Location: We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara, CA office in compliance with Everpure’s policies, unless you are on PTO, or work travel, or other approved leave

What the job involves

  • Join our agile team to shape and deliver the industry’s premier enterprise Retrieval-Augmented Generation (RAG) platform from the ground up
  • You will own end-to-end full-stack feature development at the intersection of Data and AI, partnering directly with NVIDIA engineering teams to integrate cutting-edge AI technologies
  • Operating with a high-impact startup mindset, you will drive scalable architectural solutions that empower enterprise customers with seamless, highly performant data retrieval
  • Architect & Scale Enterprise RAG Infrastructure: Design, build, and optimize robust full-stack features using Go and Python, ensuring enterprise clients retrieve, process, and query complex data with ultra-low latency
  • Pioneer Cutting-Edge GenAI Integration: Collaborate directly with NVIDIA engineering teams to integrate state-of-the-art AI tooling and model acceleration libraries, expanding platform capabilities across the evolving GenAI ecosystem
  • Drive End-to-End Product Ownership: Lead features from concept to production deployment—developing intuitive frontend interfaces and resilient backend microservices—to turn complex product requirements into seamless enterprise capabilities
  • Elevate System Performance & Quality: Establish technical standards, automated testing pipelines, and performance benchmarks to ensure high availability, security, and enterprise-grade reliability across the entire stack

The application process

  • There is no application deadline and we accept applications on an ongoing basis until the job is filled

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