{"id":2667885,"url":"https://alion.io/job/nvidia-senior-staff-site-reliability-engineer-4","title":"Senior Staff Site Reliability Engineer","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":592,"ghost_share":0.019,"stale_share":0.66,"repost_share":0.034,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"staff","employment_type":"full_time","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":{"min_usd":33000,"max_usd":76000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":823},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-09-24T00:00:00Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-18T01:32:53Z","board_verified":true,"closed_at":null,"days_open":24,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":24},"description":"NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation fueled by great technology-and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. Doing what’s never been done before takes vision, innovation, and talented people. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.\nWe are seeking a Senior Staff Software Engineer to build the runtime foundation for NVIDIA’s enterprise AI platforms. You will provide technical leadership for systems that deploy, operate, and scale AI applications, inference services, and databases across cloud and on-premises environments.\nWhat you'll be doing:\nDefine the architecture and technical roadmap for a scalable enterprise AI runtime platform.\nDesign Kubernetes-based systems for deploying, running, and scaling AI applications, inference services, and databases.\nBuild control-plane services, APIs, operators, and automation for workload provisioning, configuration, upgrades, and recovery.\nDevelop runtime capabilities for GPU scheduling, autoscaling, load balancing, and rate limiting.\nImprove the performance, availability, and developer experience of large-scale AI inference services.\nBuild and automate relational and vector database services, including provisioning, scaling, backup, and failover.\nEstablish secure and consistent application lifecycle-management patterns spanning cloud-based and on-premises platforms.\nDevelop observability tools for monitoring, profiling, and debugging applications, GPU resources, inference workloads, and databases.\nLead technical initiatives across multiple functions, mentor engineers, and establish standards for the platform’s long-term evolution.\nWhat we need to see:\nBS, MS, or PhD in Computer Science, Engineering, or a related field-or equivalent experience.\n8+ years of software engineering experience building distributed systems, cloud infrastructure, database platforms, or large-scale backend services.\nStrong programming skills in Python, Go, C++, or Java, with experience delivering production-grade systems.\nProven track record designing scalable and highly available Kubernetes-based platforms and leading technical strategy, influence across teams, and tackle complex platform problems.\nExperience building control planes, platform APIs, Kubernetes operators, or workload lifecycle-management systems.\nExperience developing high-performance services for AI inference or other low-latency workloads.\nPractical knowledge of relational or vector databases, including availability, replication, query optimization, and performance tuning.\nExperience with GitOps, CI/CD, observability, and cloud-native security practices.\n\nWays to stand out from the crowd:\nExperience building self-service platforms for application and infrastructure lifecycle management.\nExperience with inference-serving frameworks, GPU-aware scheduling, or model-performance optimization.\nExpertise in vector databases, GPU-accelerated query engines, or distributed data platforms.\nExperience supporting the complete AI application lifecycle, from development through production serving and monitoring.\nContributions to open-source projects in Kubernetes, AI/ML infrastructure, databases, distributed systems, or observability. \nNVIDIA is committed to encouraging a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.\nWidely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. 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