{"id":2912236,"url":"https://alion.io/job/amd-principal-ai-software-systems-architect","title":"Principal AI Software & Systems 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":"A","score":97,"open_postings":17,"ghost_share":0,"stale_share":0.118,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-11-08T05:47:12Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":157000,"max_usd":325000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":782},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[],"status":"closed","first_seen_at":"2026-05-26T22:11:00Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-03T14:31:17Z","board_verified":false,"closed_at":"2026-11-03T14:31:17Z","days_open":160,"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:\nAMD is seeking a Principal AI Software & Systems Architect to help drive adoption of AMD AI solutions in the on premise, enterprise environment. This role requires deep expertise in AI software stacks, inference runtimes, heterogeneous computing, and hardware-aware software architecture. You will analyze real-world AI deployments, determine how workloads should be mapped across CPUs, GPUs, NPUs, and distributed infrastructure, identify platform and ecosystem gaps, and drive the technical work required to enable successful enterprise deployments on AMD platforms. The ideal candidate can reason about AI workloads from framework to hardware and translate customer requirements into software, platform, and product direction.\nTHE PERSON:\nThe ideal candidate is a systems-oriented software architect with deep understanding of AI frameworks, accelerators, and performance engineering. You are comfortable taking a customer deployment built for another platform, determine what parts run unchanged, what parts must be modified, what parts are missing from the ecosystem, and what engineering investments are required to make the workload successful on AMD.\nYou bring:\nDeep understanding of AI workload architecture and hardware-aware software design\nExperience analyzing complex software stacks spanning frameworks, runtimes, drivers, operating systems, and hardware\nThe ability to move seamlessly between architecture, performance analysis, and technical execution\nStrong customer and ISV engagement skills with engineering-level credibility\nThe ability to influence software, hardware, and product roadmaps using real-world workload requirements\nKEY RESPONSIBILITIES\nAI Workload Analysis & Architecture\nAnalyze customer and ISV AI deployments, including models, frameworks, runtimes, serving infrastructure, and dependencies.\nDecompose workloads to identify portability, performance, scalability, and operational requirements.\nDetermine the optimal deployment architecture across client, edge, workstation, and datacenter environments.\nEvaluate how workloads should be partitioned across CPUs, GPUs, NPUs, and distributed compute resources for optimal performance and overall TCO, including modeling of the TCO for customers.\nDefine reference architectures for enterprise AI deployments and emerging AI workload patterns.\nPlatform Enablement & Optimization\nIdentify software, runtime, framework, compiler, driver, and hardware dependencies that impact deployment on AMD platforms.\nDefine and drive the technical work required to enable workloads on AMD hardware and software stacks.\nPartner with engineering teams to close ecosystem gaps, improve platform readiness, and accelerate customer adoption.\nAnalyze workload performance and identify bottlenecks related to compute, memory, communication, storage, power, and utilization.\nEstablish performance targets, validation criteria, and benchmarking methodologies to support TCO discussions.\nCustomer & ISV Technical Leadership\nServe as the technical lead for strategic customer and ISV engagements.\nConduct architecture reviews and technical assessments of AI deployments.\nGuide customers and partners through workload migration, platform selection, enablement, and optimization activities.\nDevelop reusable deployment patterns, best practices, and technical guidance that can be applied across multiple engagements.\nProduct & Platform Strategy\nTranslate real-world workload requirements into software, platform, and hardware requirements.\nInfluence AMD roadmap priorities through direct engagement with customers, ISVs, and ecosystem partners.\nIdentify emerging AI deployment trends and opportunities across client, edge, workstation, and datacenter markets.\nHelp shape AMD's long-term AI platform strategy through workload-driven insights and technical leadership.\nPREFERRED QUALIFICATIONS\nDeep understanding of AI inference systems, model serving architectures, AI infrastructure, and performance optimization in production environments.\nStrong understanding of AI software stacks, including frameworks, runtimes, compilers, drivers, and accelerator libraries.\nExperience analyzing and optimizing software across multiple layers of the stack, from application and framework behavior through runtime, operating system, driver, and hardware interactions.\nStrong understanding of heterogeneous computing architectures and workload partitioning across CPUs, GPUs, NPUs, and distributed compute resources.\nExperience evaluating workload characteristics such as latency, throughput, memory footprint, communication patterns, scalability, power efficiency, and total cost of ownership (TCO).\nExperience enabling, optimizing, porting, or debugging software on GPU or other accelerator platforms.\nAbility to decompose complex customer deployments, identify software and platform dependencies, and define the technical work required to achieve successful deployment on a new platform.\nExperience leading technical discussions with customers, ISVs, and internal engineering teams.\nACADEMIC CREDENTIALS:\nBachelor’s or Master'sdegree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\nLOCATIONS:\nAustin, TX.\nBoxborough, MA.\nMarkham, Ontario, CA.\nThis role is not eligible for visa sponsorship.\n#LI-CB1\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:\nAMD is seeking a Principal AI Software & Systems Architect to help drive adoption of AMD AI solutions in the on premise, enterprise environment. This role requires deep expertise in AI software stacks, inference runtimes, heterogeneous computing, and hardware-aware software architecture. You will analyze real-world AI deployments, determine how workloads should be mapped across CPUs, GPUs, NPUs, and distributed infrastructure, identify platform and ecosystem gaps, and drive the technical work required to enable successful enterprise deployments on AMD platforms. The ideal candidate can reason about AI workloads from framework to hardware and translate customer requirements into software, platform, and product direction.\nTHE PERSON:\nThe ideal candidate is a systems-oriented software architect with deep understanding of AI frameworks, accelerators, and performance engineering. You are comfortable taking a customer deployment built for another platform, determine what parts run unchanged, what parts must be modified, what parts are missing from the ecosystem, and what engineering investments are required to make the workload successful on AMD.\nYou bring:\nDeep understanding of AI workload architecture and hardware-aware software design\nExperience analyzing complex software stacks spanning frameworks, runtimes, drivers, operating systems, and hardware\nThe ability to move seamlessly between architecture, performance analysis, and technical execution\nStrong customer and ISV engagement skills with engineering-level credibility\nThe ability to influence software, hardware, and product roadmaps using real-world workload requirements\nKEY RESPONSIBILITIES\nAI Workload Analysis & Architecture\nAnalyze customer and ISV AI deployments, including models, frameworks, runtimes, serving infrastructure, and dependencies.\nDecompose workloads to identify portability, performance, scalability, and operational requirements.\nDetermine the optimal deployment architecture across client, edge, workstation, and datacenter environments.\nEvaluate how workloads should be partitioned across CPUs, GPUs, NPUs, and distributed compute resources for optimal performance and overall TCO, including modeling of the TCO for customers.\nDefine reference architectures for enterprise AI deployments and emerging AI workload patterns.\nPlatform Enablement & Optimization\nIdentify software, runtime, framework, compiler, driver, and hardware dependencies that impact deployment on AMD platforms.\nDefine and drive the technical work required to enable workloads on AMD hardware and software stacks.\nPartner with engineering teams to close ecosystem gaps, improve platform readiness, and accelerate customer adoption.\nAnalyze workload performance and identify bottlenecks related to compute, memory, communication, storage, power, and utilization.\nEstablish performance targets, validation criteria, and benchmarking methodologies to support TCO discussions.\nCustomer & ISV Technical Leadership\nServe as the technical lead for strategic customer and ISV engagements.\nConduct architecture reviews and technical assessments of AI deployments.\nGuide customers and partners through workload migration, platform selection, enablement, and optimization activities.\nDevelop reusable deployment patterns, best practices, and technical guidance that can be applied across multiple engagements.\nProduct & Platform Strategy\nTranslate real-world workload requirements into software, platform, and hardware requirements.\nInfluence AMD roadmap priorities through direct engagement with customers, ISVs, and ecosystem partners.\nIdentify emerging AI deployment trends and opportunities across client, edge, workstation, and datacenter markets.\nHelp shape AMD's long-term AI platform strategy through workload-driven insights and technical leadership.\nPREFERRED QUALIFICATIONS\nDeep understanding of AI inference systems, model serving architectures, AI infrastructure, and performance optimization in production environments.\nStrong understanding of AI software stacks, including frameworks, runtimes, compilers, drivers, and accelerator libraries.\nExperience analyzing and optimizing software across multiple layers of the stack, from application and framework behavior through runtime, operating system, driver, and hardware interactions.\nStrong understanding of heterogeneous computing architectures and workload partitioning across CPUs, GPUs, NPUs, and distributed compute resources.\nExperience evaluating workload characteristics such as latency, throughput, memory footprint, communication patterns, scalability, power efficiency, and total cost of ownership (TCO).\nExperience enabling, optimizing, porting, or debugging software on GPU or other accelerator platforms.\nAbility to decompose complex customer deployments, identify software and platform dependencies, and define the technical work required to achieve successful deployment on a new platform.\nExperience leading technical discussions with customers, ISVs, and internal engineeri...","description_format":"text","description_chars":13215,"description_truncated":true,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Computer Components","AI Chips & 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