{"id":3695160,"url":"https://alion.io/job/nvidia-senior-technical-program-manager-dgx-cloud-software-products-and-services-2","title":"Senior Technical Program Manager, DGX Cloud Software Products and Services","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":84,"open_postings":806,"ghost_share":0.024,"stale_share":0.568,"repost_share":0.048,"time_to_fill_p50_days":40,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Product","role_family":"Product","seniority":"senior","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":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Jira","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Quantization","optional":false},{"name":"SGLang","optional":false},{"name":"SLURM","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"vLLM","optional":false},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-11-02T00:00:00Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-06T00:20:33Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"NVIDIA’s DGX Cloud (DGXC) supports AI for key research and product tasks. The Exemplar Performance Program is central to this goal. It guides all CSP and NCP partners toward achieving outstanding performance and shifts the focus from GPU cost per hour to total workload cost of ownership. Exemplar provides a clear, consistent measure of what NVIDIA hardware and software achieve at scale. It sets the benchmark for cloud partners and challenges inaccurate GPU comparisons made by analysts.\nWe seek a Senior Technical Program Manager to handle daily operations for the Exemplar Performance Program. You will convert priorities into synchronized capacity, validation, debugging, and release plans across CSPs, NVIDIA Cloud Partners (NCPs), and internal engineering groups. Your role includes managing workstreams that cover Slurm and Kubernetes-based training and inference benchmarking, cross-partner debugging, release and QA coordination, PLC/OSRB alignment, and program visibility simultaneously. As the program expands into inference and agentic AI workloads, you will apply these methods to new stack complexities and partner engagements. You will collaborate directly with the program and Product lead to ensure execution aligns with Roadmaps. This position demands solid technical expertise, initiative, and the capability to work well with engineering, product, and partner-facing groups at different levels of the company. The ideal applicant has a deep understanding of cloud infrastructure and inference systems. They can ask insightful questions, lead investigations to resolution, and turn technical obstacles into concise action steps!\nWhat You’ll Be Doing:\nMaintain the demand and allocation levels across platforms, GPU counts, topologies, and workloads; coordinate capacity reservations, access, readiness checks, and debug windows with cluster owners.\nTrack cross-CSP performance investigations with engineering, SAs, and partner teams and build playbooks and pre-flight checks for repeat offenders.\nMaintain a coordinated achievement and coverage plan across recipes, frameworks, results tooling, and QA; follow up on MR reviews, merges, dependencies, and blocking regressions, and prepare release readiness summaries for each program increment.\nHelp connect software roadmap execution to full-stack readiness, including dependencies across infrastructure, bring-up, validation, and downstream operational support.\nStandardize intake, debug handoffs, and release evidence practices; extend them from training into inference, K8s, and agentic benchmarking as priorities evolve.\nEstablish engineering and product rhythm for Product Life Cycle (PLC) achievements and monthly release cadences.\nIdentify multi-functional dependencies, mitigate risks, and drive resolution of complex technical and programmatic issues across partner, engineering, and product teams.\nDevelop and maintain metrics for program efficiency and delivery health; collect and analyze data to support planning and data-driven decisions, and communicate progress clearly to senior leadership.\nWhat We Need to See:\n8+ years of technical program management experience. A Bachelor’s degree or equivalent experience to this in Computer Science, Electrical Engineering, AI, or a related field is required. You must have demonstrated ability to manage programs across multiple time zones and organizations.\nPractical knowledge of inference systems, cloud platforms, and distributed computing - sufficient to pose relevant technical questions and interpret engineering updates directly.\nTrack record managing complex, multi-stakeholder programs in fast-paced software development environments, from kickoff through partner-facing delivery.\nBackground in software release management, QA coordination, and platform validation cycles - preferably including compliance or review routines like open-source review, security review, or PLC/OSRB.\nStrong written communication skills; ability to write crisp, executive-ready program status updates and blocking issue memos that lead with signal, not noise.\nExperience with large-scale Agile tools and reporting (Jira, NVBugs, or equivalent) and comfort defining your own tracking structure when one doesn’t exist.\nWays to Stand Out from the Crowd:\nStrong background in Machine Learning, Deep Learning, and Artificial Intelligence applications, with familiarity with AI benchmarking tools, evaluation frameworks, or performance scorecards for large-scale GPU workloads!\nExperience working with LLM inference frameworks like vLLM, SGLang, or TensorRT-LLM, or knowledge of inference optimization methods such as speculative decoding, quantization, disaggregated prefill/decode, or multi-token prediction.\nPrior experience supporting CSP or NCP partner programs, including coordinating platform validations, cluster capacity requests, or performance bring-up across organizational boundaries.\nKubernetes or cloud-native workload experience, with an understanding of how container orchestration affects GPU placement, scheduling, and workload repeatability.\nExperience with open-source software release procedures, including contributor licensing, OSRB-style assessments, and ecosystem readiness, to bring internal tooling public in a compliant, organized way.\nWidely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/\nYou will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until November 6, 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. 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