{"id":2912246,"url":"https://alion.io/job/amd-principalsenior-robotics-ai-architect","title":"Principal/Senior Robotics AI Architect","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":75,"open_postings":163,"ghost_share":0,"stale_share":0.994,"repost_share":0,"time_to_fill_p50_days":28,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Robotics","role_family":"Robotics","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":182000,"max_usd":351000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":37},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Lighthouse","optional":false},{"name":"Motion Planning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Physical AI","optional":false},{"name":"ROS2","optional":false},{"name":"Sensor Fusion","optional":false},{"name":"Vercel AI SDK","optional":false},{"name":"GStreamer","optional":true},{"name":"OpenCV","optional":true},{"name":"Sim-to-Real","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-05-18T23:57:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-24T18:45:49Z","board_verified":true,"closed_at":null,"days_open":158,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":158},"description":"WHAT YOU DO AT AMD CHANGES EVERYTHING\nAt AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gamingand embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuityand a shared passion to create something extraordinary. When you join AMD, you’lldiscover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.Together, we advance your career.\nTHE ROLE:\nWe are seeking a Robotics AI Architect to define and scale next-generation Physical AI systems, with a focus on complex robotic platforms (including humanoids). This role emphasizes architectural leadership across multi-layer AI control loops and tight collaboration with lighthouse customers to achieve production-grade performance targets.\nTHE PERSON:\nAs a key technical authority, you will synthesize learnings from real-world deployments and translate them into platform-defining capabilities, shaping the roadmap for our AI SDKs, runtime, and reference architectures to enable broad ecosystem scalability.\nKEY RESPONSIBILITIES:\nEnd-to-End AI Control Loop Architecture (Core Focus)\nDefine architecture for hierarchical AI control loops, including:\nPerception (sensor fusion, VLMs, state estimation)\nWorld modeling and scene understanding\nTask and motion planning\nLow-latency control and actuation\nLearning and adaptation loops\nEstablish timing models and system-level constraints:\nDeterministic execution for control loops (µs-ms)\nBounded latency for perception/planning (ms-scale)\nGuide architectural decisions to:\nMinimize latency, jitter, and data movement\nOptimize compute utilization across heterogeneous systems\nInfluence compute-software co-design across CPU, GPU, and accelerators\nLighthouse Customer Co-Engineering\nAct as architectural lead for strategic/lighthouse customers, guiding:\nSystem design decisions\nPerformance trade-offs\nDeployment architecture\nInfluence customer implementations to align with:\nPlatform best practices\nScalable architectural patterns\nTranslate real-world constraints (latency, power, safety) into:\nPlatform requirements\nArchitecture refinements\nLead deep technical engagements, including:\nArchitecture and design reviews\nPerformance tuning strategies\nSystem-level debugging approaches\nInfluencing Robotics Reference Architectures, Platform Architecture & SDKs \nDefine reference architecture for complex robotic systems (humanoids, high-DoF manipulators, mobile manipulation platforms), establishing industry-leading blueprints for Physical AI systems\nInfluence architectural partitioning strategies across:\nOn-robot compute (real-time loops)\nEdge/accelerator subsystems\nCloud (training, simulation, fleet learning)\nProvide architectural guidance on:\nWhole-body control integration\nLocomotion and balance systems\nDexterous manipulation pipelines\nMulti-modal perception stacks\nServe as a bridge between lighthouse deployments and platform evolution, translating system-level insights into:\nSDK feature direction\nRuntime and middleware enhancements\nReference pipeline abstractions\nShape the roadmap of:\nPhysical AI SDK and runtime frameworks\nRobotics middleware integrations (ROS2 and beyond)\nDataflow and scheduling architectures for deterministic execution\nIdentify systemic gaps and influence solutions in:\nScheduling and orchestration models\nMemory and dataflow efficiency\nInter-process/inter-node communication\nReal-time guarantees and QoS mechanisms\nDrive the creation of scalable architectural patterns, including:\nReusable operator graphs and pipelines\nStandardized deployment topologies\nBenchmark and validation frameworks\nEnsure that lighthouse customer learnings are abstracted and generalized into:\nRepeatable reference architectures\nPlatform capabilities consumable across a wide customer base\nPREFERRED EXPERIENCE:\nExperience in Robotics, Autonomous systems AI architecture, definition and development, RL work, Sim-to-real, cloud-to-sim, real-to-sim/cloud from AI perspective.\nProven technical leadership experience influencing external and internal stakeholders\nDeep understanding of:\nAI inference runtimes and deployment tradeoffs\nSystem architecture level CPU/GPU/NPU scheduling and contention\nSystem-level performance, latency, and isolation\nSoftware frameworks and usage (multimedia, ROS2, OpenCV, gstreamer etc.)\nIndustry leading SW inference frameworks (vLLM etc.), runtimes, tools\nPerformance bottleneck, characterization\nDeterminism, real-time and safety considerations in mixed-criticality systems\nAbility to engage credibly with customer’s engineering leaders, AI architects\nTrack record of transforming customer deployments into platform and roadmap feedback\nHands-on architects who can guide engineers, debug problems, create innovative PoCs as well as abstract unnecessary details for executive presentations\nFamiliarity/experience with AMD GPU and NPU AI SW stacks and tools will be a plus\nACADEMIC CREDENTIALS:\nBachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field \nThis role is not eligible for visa sponsorship.\n#LI-JG1\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nWe are seeking a Robotics AI Architect to define and scale next-generation Physical AI systems, with a focus on complex robotic platforms (including humanoids). This role emphasizes architectural leadership across multi-layer AI control loops and tight collaboration with lighthouse customers to achieve production-grade performance targets.\nTHE PERSON:\nAs a key technical authority, you will synthesize learnings from real-world deployments and translate them into platform-defining capabilities, shaping the roadmap for our AI SDKs, runtime, and reference architectures to enable broad ecosystem scalability.\nKEY RESPONSIBILITIES:\nEnd-to-End AI Control Loop Architecture (Core Focus)\nDefine architecture for hierarchical AI control loops, including:\nPerception (sensor fusion, VLMs, state estimation)\nWorld modeling and scene understanding\nTask and motion planning\nLow-latency control and actuation\nLearning and adaptation loops\nEstablish timing models and system-level constraints:\nDeterministic execution for control loops (µs-ms)\nBounded latency for perception/planning (ms-scale)\nGuide architectural decisions to:\nMinimize latency, jitter, and data movement\nOptimize compute utilization across heterogeneous systems\nInfluence compute-software co-design across CPU, GPU, and accelerators\nLighthouse Customer Co-Engineering\nAct as architectural lead for strategic/lighthouse customers, guiding:\nSystem design decisions\nPerformance trade-offs\nDeployment architecture\nInfluence customer implementations to align with:\nPlatform best practices\nScalable architectural patterns\nTranslate real-world constraints (latency, power, safety) into:\nPlatform requirements\nArchitecture refinements\nLead deep technical engagements, including:\nArchitecture and design reviews\nPerformance tuning strategies\nSystem-level debugging approaches\nInfluencing Robotics Reference Architectures, Platform Architecture & SDKs \nDefine reference architecture for complex robotic systems (humanoids, high-DoF manipulators, mobile manipulation platforms), establishing industry-leading blueprints for Physical AI systems\nInfluence architectural partitioning strategies across:\nOn-robot compute (real-time loops)\nEdge/accelerator subsystems\nCloud (training, simulation, fleet learning)\nProvide architectural guidance on:\nWhole-body control integration\nLocomotion and balance systems\nDexterous manipulation pipelines\nMulti-modal perception stacks\nServe as a bridge between lighthouse deployments and platform evolution, translating system-level insights into:\nSDK feature direction\nRuntime and middleware enhancements\nReference pipeline abstractions\nShape the roadmap of:\nPhysical AI SDK and runtime frameworks\nRobotics middleware integrations (ROS2 and beyond)\nDataflow and scheduling architectures for deterministic execution\nIdentify systemic gaps and influence solutions in:\nScheduling and orchestration models\nMemory and dataflow efficiency\nInter-process/inter-node communication\nReal-time guarantees and QoS mechanisms\nDrive the creation of scalable architectural patterns, including:\nReusable operator graphs and pipelines\nStandardized deployment topologies\nBenchmark and validation frameworks\nEnsure that lighthouse customer learnings are abstracted and generalized into:\nRepeatable reference architectures\nPlatform capabilities consumable across a wide customer base\nPREFERRED EXPERIENCE:\nExperience in Robotics, Autonomous systems AI architecture, definition and development, RL work, Sim-to-real, cloud-to-sim, real-to-sim/cloud from AI perspective.\nProven technical leadership experience influencing external and internal stakeholders\nDeep understanding of:\nAI inference runtimes and deployment tradeoffs\nSystem architecture level CPU/GPU/NPU scheduling and contention\nSystem-level performance, latency, and isolation\nSoftware frameworks and usage (multimedia, ROS2, OpenCV, gstreamer etc.)\nIndustry leading SW inference frameworks (vLLM etc.), runtimes, tools\nPerformance bottleneck, characterization\nDeterminism, real-time and safety considerations in mixed-criticality systems\nAbility to engage credibly with customer’s engineering leaders, AI architects\nTrack record of transforming customer deployments into platform and roadmap feedback\nHands-on architects who can guide engineers, debug problems, create innovative PoCs as well as abstract unnecessary details for executive presentations\nFamiliarity/experience with AMD GPU and NPU AI SW stacks and tools will be a plus\nACADEMIC CREDENTIALS:\nBachelor’s or Master’s in Electrical Engineer, Computer Engineering, Computer Science, or a closely related field \nThis role is not eligible for visa sponsorship.\n#LI-JG1\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. 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