Principal AI Infrastructure & Accelerator Architect

Are you a visionary technical leader passionate about defining the future of AI infrastructure and squeezing every drop of performance out of advanced hardware accelerators at scale? We are seeking a Principal Architect to lead, shape, and execute our technical strategy for AI performance, optimization, and hardware-software co-design.

In this elite, highly visible role, you will define the architectural vision for both AI training and serving infrastructure, delivering massive industry-wide impact. You will spearhead our Center of Excellence (CoE), scaling our practice and guiding the technical roadmap across next-generation Tensor Processing Units (TPUs), Graphics Processing Unit (GPU) fleets, state-of-the-art ML models, and advanced compiler toolchains.

Your architectural decisions will directly enable cutting-edge AI research and large-scale production deployments across Google Cloud, major enterprise customers, and the broader open-source ecosystem. If you thrive on solving intractable performance bottlenecks and redefining what is physically and computationally possible in AI infrastructure, this is your platform.

Responsibilities

• Define and drive the multi-year technical roadmap for high-performance AI kernels, custom operations, and hardware-software co-design targeting TPU and GPU architectures

• Scale and mentor a world-class technical practice, establishing architectural governance, engineering standards, and best practices across the organization

• Act as the principal technical liaison partnering with ML researchers, core framework architects (JAX, PyTorch), and compiler engineering teams (XLA, MLIR) to eliminate systemic bottlenecks and shape future hardware/software requirements

• Architect foundational infrastructure-including enterprise-grade benchmarking suites, automated autotuning frameworks, regression analysis pipelines, and comprehensive documentation-empowering the global developer community

• Anticipate industry shifts by tracking advancements in hardware architectures, emerging model topologies, and compiler innovations to unlock step-changes in AI training and inference efficiency

• Bachelors degree in Computer Science, Electrical Engineering, or equivalent practical experience (Masters or Ph.D. preferred)

• 15+ years of software engineering experience, with 8+ years focused on distributed systems, AI infrastructure, or high-performance computing (HPC) architecture

• 7+ years of experience designing and developing complex software systems in C++ or Python

• 5+ years of experience leading the architecture, design, and delivery of large-scale software products, frameworks, or developer ecosystems from inception to production

• Proven track record of architecting performance-critical systems at the kernel level, bridging hardware accelerators and high-level software frameworks

Nice to have

• Deep expertise in optimizing TPU/GPU execution, leveraging low-level kernel languages/abstractions such as Pallas, Mosaic, Triton, or CUDA

• Comprehensive knowledge of modern ML frameworks (JAX, PyTorch), attention mechanisms, Mixture of Experts (MoEs), model quantization, and low-precision arithmetic

• Advanced understanding of modern accelerator architectures, including heterogeneous compute, complex memory hierarchies, data movement optimization, and multi-node scale-out fabrics

• Deep familiarity with compiler principles, code generation, and modern toolchains such as MLIR, OpenXLA, and LLVM

• Demonstrated leadership in building and scaling developer infrastructure, widely adopted Open-Source Software (OSS) libraries, and extensible high-performance APIs

• Exceptional strategic communication and stakeholder management skills, with a history of influencing cross-functional engineering teams, researchers, and executive leadership

• Medical, Dental and Vision Insurance (Subsidized)

• Health Savings Account

• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)

• Short-Term and Long-Term Disability (Company Provided)

• Life and AD&D Insurance (Company Provided)

• Employee Assistance Program

• Unlimited access to LinkedIn learning solutions

• Matched 401(k) Retirement Savings Plan

• Paid Time Off - the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)

• Paid Holidays - nine (9) total per year

• Legal Plan and Identity Theft Protection

• Accident Insurance

• Employee Discounts

• Pet Insurance

• Employee Stock Purchase Program

• If otherwise eligible, participation in the discretionary annual bonus program

• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program