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Sovereign AI Field Application Engineer

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AMD

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Location:
United Kingdom

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

We are seeking a Senior Field Application Engineer (FAE) to join the Centre of Excellence (CoE) to lead the AI discussion and demonstration within the worlds largest national labs and sovereign AI centres. The role broadly involves; Providing technical AI positioning and Proof of Concepts for AI factories, Gigafactories and other Sovereign AI customers at both application and systems level; ‘Hands-on’ engineering investigations to understand both performance and characteristic performance across popular and customer-specific training and inference workloads; Owning the technical interface into the customer and qualification. Working closely with sales and partners to position AMD solutions. Understanding concerns and blockers; Positioning AMD Instinct GPUs, EPYC CPUs and our new ‘AI smart NICs’

Job Responsibility:

  • Support winning new AI business in national AI and HPC centres. Enabling customers to execute their AI workloads on AMD Instinct GPUs, EPYC CPUs, and AI NICs. Supporting partners in RFP responses by testing requested workloads
  • Owning technical qualification of the customer, partnering with Sales and Business Unit orgs
  • Demonstrate and advise customers and partners through Proof of Concepts, presentations, and training
  • Engineering: execute popular and customer-driven AI inference and training workloads, generate results and create a characteristic understanding of AI performance on AMD hardware. Understand how system and software choices affect performance. Compare performance to our competition
  • Run training and inference performance investigations using common frameworks (Pytorch, Tensorflow, JAX) and using MLperf, Hugging Face etc
  • Build a body of documentation for internal and external dissemination: AMD-internal guides, whitepapers, tuning guides, training collateral
  • Provide onsite training
  • Proactive engagement across AMD teams: GPU Business Unit, Engineering, Architecture, Platform, Software, and Product Development teams providing feedback and leadership from the field on requirements. Gathering missing functionality and working with Engineering to resolve and test
  • Assist in creating Total Cost of Ownership models to aid pricing with bid desk
  • Technically owning and resolving customer and partner issues. Submitting JIRA tickets and driving resolution

Requirements:

  • Demonstrable hands-on expertise working with either popular AI frameworks and models on GPU
  • Experience leading large technical programs or opportunities
  • Strong systems background. Understands and can quantify the impact of system architecture on performance
  • Strong positive can-do attitude willing to do what is necessary and lead others in the wider FAE team by example. Available to help colleagues
  • Skilled in independently prioritizing opportunities to deliver results on time
  • Excellent verbal and written communication skills
  • Based in Europe ideally EU zone
  • Open to travel both domestic and international, approximately 10-20% over a year. Anticipate a ramp period with increased travel at the start
  • Bachelors' Degree in a technical field (Computer Science, Electrical Engineering, Physics, Mathematics) preferred

Nice to have:

  • Hands-on AI and HPC experience within large national HPC centres
  • Programming experience with any of HIP, CUDA, Python, C/C++, Fortran, OpenACC, OpenMP, pSTL
  • Understanding impact of inter-node network choices on performance at scale. Creating performance projections for applications
  • Deep Neural Networks and their design for different Machine Learning cases
  • Any experience understanding/inspecting/writing assembly
  • Understanding of memory and cache hierarchy and methods to query performance/latency at each level. Inspecting and dataflow down to the register-level
  • Government level security clearance

Additional Information:

Job Posted:
March 26, 2026

Employment Type:
Fulltime
Work Type:
Remote work
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