Sr. Post-Silicon Systems Validation Engineer, Annapurna Labs

Sr. Post-Silicon Systems Software Validation Engineer, Annapurna Labs

Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before.

Join our Silicon Validation team to validate next-generation machine learning accelerators that power AWS's cloud computing infrastructure. You'll work in a fast-paced, startup-like environment alongside some of the brightest minds in the industry on cutting-edge, internet-scale technology that directly impacts how customers use Machine Learning acceleration. We are changing the landscape of cloud infrastructure by accelerating the development of custom silicon by moving beyond traditional partnerships to dominate in AI training and inference.

Your work will span validation of the complete vertical stack—silicon, PCB, high-speed components (HBM, PCIe, chip-to-chip), inter-system connections, and system-to-system interfaces. You'll dive deep into new technology hardware components and scaling technologies that power our Machine Learning boards and servers at scale, ensuring every component of our hardware and software comes together into products our customers rely on.

• Lead and own critical validation aspects across the entire product development lifecycle—from early design validation through emulation, silicon bring‑up, post‑silicon validation, and ongoing support of production systems deployed in AWS data centers.
• Collaborate deeply with architecture, RTL design, design verification, firmware, and software teams to ensure our next‑generation AI/ML accelerators meet the highest standards of quality and performance.
• Bridge multiple domains and broad scope of impact—from low‑level hardware interfaces to high‑level ML workloads—to deliver exceptional results.

• Strong programming skills (Python, Lua, C/C++, Rust, Go, etc).
• A solid understanding of computer architecture and chip/system validation methodologies.
• Experience with cloud infrastructure and CI/CD.
• Firmware testing and/or development (BIOS, BMC, drivers).
• Domain expertise in any of these areas: PCIe, HBM, GPUs, neural networks, ML HW architecture.
• Knowledge of the full validation lifecycle from RTL simulation (System Verilog/UVM, VCS, Questa, Xcelium) and emulation (Palladium, Zebu, Veloce) through silicon failure analysis and debug.

• Develop comprehensive validation strategies and lead new methodologies to improve validation coverage and time to root cause.
• Create detailed test plans covering functional, performance, power, and stress testing from silicon bring‑up to product release.
• Mentor and provide direction to junior validation engineers.
• Execute complex test plans from RTL simulation and emulation environments through physical silicon validation.
• Handle complex debug including hands‑on silicon bring‑up and debug in the lab using oscilloscopes, logic analyzers, and protocol analyzers.
• Validate ML accelerator performance, accuracy, and reliability using real‑world neural network workloads.
• Build test infrastructure, CI/CD, and automated regression frameworks to enable efficient validation at scale.
• Collaborate across architecture, design, firmware, and software teams to triage failures and drive root‑cause analysis to closure.
• Review test results, identify patterns, and provide feedback to improve design quality and validation coverage.
• Deliver new tests to production systems in AWS data centers and manufacturing to improve fleet health.

• 5+ years of programming with at least one software programming language experience.
• Bachelor's degree or above in computer science, computer engineering, or related field.
• 5+ years of non‑internship system test development, code reviews, source control management, build processes, automated deployments, and operations experience.
• Experience with Linux environments and Git.
• Experience with server hardware and debug tools.