{"id":1599031,"url":"https://alion.io/job/nvidia-engineering-manager-ai-platform-sre","title":"Engineering Manager – AI Platform & SRE","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":"A","score":89,"open_postings":299,"ghost_share":0.017,"stale_share":0.381,"repost_share":0.033,"time_to_fill_p50_days":29,"computed_at":"2026-10-03T05:45:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":208000,"max":333500,"currency":"USD","period":"year","gross":null,"usd_annual":333500},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Incident Management","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-01T18:49:34Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-04T00:54:03Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Site Reliability Engineering (SRE) at NVIDIA is an engineering field focused on designing, building, and operating large-scale production systems with exceptional reliability, efficiency, and availability. It combines software and systems engineering practices with expertise across distributed systems, networking, Kubernetes, public cloud, observability, capacity management, continuous delivery, and automation.\nAs an Engineering Manager, you will lead a team of dedicated engineers responsible for building and operating resilient AI platform capabilities at enterprise scale. You will combine people leadership with strong technical judgment, helping the team translate ambiguous business and engineering challenges into a clear strategy and executable roadmap. You will partner across Cloud, Platform, Security, and AI/ML organizations to deliver reliable systems, improve developer productivity, and advance the use of AI agents and skills in platform operations.\nOur culture values diversity, intellectual curiosity, collaboration, and continuous learning. We encourage thoughtful risk-taking, blameless analysis, and shared ownership. You will create an environment in which engineers can do their best work, grow their careers, and make a meaningful impact.\nWhat you’ll be doing\nLead, develop, and grow a team of SRE, platform, and software engineers responsible for NVIDIA’s AI Platform Runtime and related production services.\nDefine the team’s technical strategy, priorities, and roadmap in alignment with broader product, platform, and business objectives.\nGuide the design and delivery of highly available, scalable, secure, and resilient distributed systems that support enterprise AI agent products.\nDrive the development of AI agents, AI skills, and intelligent automation for platform operations, incident response, troubleshooting, and remediation.\nEstablish measurable reliability goals and effective operational practices using service-level indicators, service-level objectives, error budgets, capacity models, operational health metrics, and production readiness reviews.\nImprove engineering velocity and developer experience through self-service platforms, infrastructure-as-code, standardized delivery patterns, and automation.\nPartner with product managers, architects, and leaders across Cloud, Security, Networking, Platform, and AI/ML teams to coordinate initiatives involving multiple functions.\nMaintain a healthy balance among feature delivery, platform investment, operational work, reliability improvements, and technical debt reduction.\nLead the team through critical incidents and ensure that blameless postmortems result in clear ownership and durable corrective actions.\nRecruit exceptional engineers and foster an inclusive, high-performing environment through coaching, feedback, career development, and thoughtful delegation.\nWhat we need to see\n10+ years of experience in Site Reliability Engineering, Platform Engineering, Software Engineering, Cloud Infrastructure, or a related technical field, including 3+ years managing or formally leading engineering teams responsible for complex production systems.\nTechnical foundation in distributed systems, Linux, networking, Kubernetes, and public cloud platforms such as AWS, Azure, or GCP.\nExperience leading teams that build production software and automation using languages such as Python, Go, TypeScript, JavaScript, or Java.\nSolid understanding of observability at scale, including OpenTelemetry, metrics, logs, distributed tracing, profiling, and operational analytics.\nExperience applying SRE practices such as service-level objectives, error budgets, capacity and resource management, incident management, disaster recovery, and blameless postmortems.\nDemonstrated ability to create technical roadmaps, manage competing priorities, and deliver measurable outcomes across multiple teams.\nProven ability to hire, coach, retain, and develop engineers at different career stages.\nOutstanding communication and collaboration skills, with the ability to influence across technical, product, and organizational boundaries.\nWays to stand out from the crowd\nHands-on experience with AI agents, agentic workflows, or intelligent automation for infrastructure and production operations.\nA track record of improving availability, performance, operational efficiency, developer productivity, or incident response through measurable engineering initiatives.\nExperience building or scaling an SRE or platform engineering function across a large enterprise and coordinating complex programs across organizational boundaries.\nSuccess developing senior engineers and technical leaders, paired with a strong sense of ownership, curiosity, and empathy that enables you to build trust and bring clarity to ambiguity.\nNVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens new universes to explore, enables outstanding creativity and discovery, and powers innovations that were once science fiction, from artificial intelligence to autonomous vehicles.\nNVIDIA is looking for exceptional engineering leaders like you to build the teams and platforms that will accelerate the next wave of artificial intelligence.\nWidely considered to be one of the technology world’s most desirable employers,\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until October 5, 2026.This posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering an inclusive 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.","description_format":"text","description_chars":6322,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Servers & Data Center Hardware","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-01T18:49:34Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":29,"reasons":["conf:6","velocity","win:early","comp:brand"],"computed_at":"2026-10-03T05:45:00Z"},"pay":{"stated_usd_annual":333500,"is_top_pay":true},"html_url":"https://alion.io/job/nvidia-engineering-manager-ai-platform-sre","json_url":"https://alion.io/job/nvidia-engineering-manager-ai-platform-sre.json","meta":{"generated_at":"2026-10-04T02:20:46Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3322,"day_limit":5000,"remaining_today":1678,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}