{"id":4233037,"url":"https://alion.io/job/netapp-software-engineer-35","title":"Software Engineer","company":{"id":58700,"name":"NetApp","domain":"netapp.com","url":"https://alion.io/company/netapp","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":90,"open_postings":32,"ghost_share":0,"stale_share":0.375,"repost_share":0.031,"time_to_fill_p50_days":54,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Edge AI","optional":false},{"name":"Gradio","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Streamlit","optional":false}],"status":"live","first_seen_at":"2026-11-09T17:35:47Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-13T10:52:39Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Job Summary\nNetApp's Chief Platform and Technology Office (CPTO) is hiring AI/ML Engineers to design and build incubation projects that shape NetApp's technology strategy. You will take AI agents, LLM-powered systems, and RAG pipelines from prototype to production. You will also build the React front ends and Python services that put them in users' hands.You bring 2-5 years of hands-on experience deploying AI/ML solutions in production. You have deep expertise in AI agents, LLM integration and optimization, RAG architectures, and modern ML frameworks. You are fluent in Python and comfortable building user-facing applications in React, with Streamlit or Gradio for fast prototypes. Go is a useful addition. Experience in the storage or cloud domain is a strong plus.We value clear communicators who care about responsible AI, quality, and meeting deadlines.\nJob Requirements\nBuild AI agents that reason, plan, use tools, and execute multi-step tasks.\nOptimize LLM-powered systems, including token optimization, cost-efficient inference, prompt engineering frameworks, and caching.\nBuild and scale advanced RAG pipelines with hybrid search, re-ranking, agentic retrieval, and dynamic knowledge base integration.\nFine-tune and customize foundation models for domain-specific use cases in storage, cloud infrastructure, and enterprise operations.\nDevelop and maintain MLOps pipelines for model training, evaluation, deployment, and monitoring at scale.\nBuild React front ends for AI products, such as chat and agent interfaces, streaming responses, and dashboards that show agent reasoning, retrieval sources, and evaluation results.\nDevelop Python back-end services and APIs that connect the UI to agents, retrieval layers, and model endpoints, and use Streamlit or Gradio to turn ideas into working demos quickly.\nPackage and ship full stack applications with Docker and Kubernetes, supported by CI/CD, observability, and automated tests.\nBuild fault-tolerant, low-latency distributed systems for real-time AI inference, and explore multi-modal AI, edge inference, and distributed training.\nContribute to POCs and incubation projects that shape NetApp's AI/ML roadmap, working with engineers, data scientists, and product teams from problem definition through deployment and early customer support.\nEducation\n2-5 years of experience deploying AI/ML solutions in production.\nStrong Python skills, including building APIs and back-end services.\nWorking experience with React and PythonHands-on experience with AI agents, LLM integration, prompt engineering, and RAG architectures.\nBachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or 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