Everpure Applied AI
Fullstack Software Engineer, AI Infra
- Location Santa Clara, California
- Seniority senior
- Posted 2026-08-31
Original posting ↗ You apply on the company site — we never collect applications.
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role details
Design, build, and optimize full-stack features using Go and Python to enable enterprise clients to retrieve and process complex data with low latency.
Summary generated by AI from the original posting.
Hard requirements to check first
- Clearance：not mentioned in the posting
- Work auth：not mentioned in the posting
Skills
PythonGoRAGNVIDIAGenAILLMAI/ML-driven architecturesBackend microservices
Excerpt from the original posting
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. 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. THE ROLE 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. WHAT YOU'LL DO - 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. WHAT YOU BRING - 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 & Init…