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# Datacenter & Agentic AI Workload Performance Analysis Engineer

- **Company:** Tenstorrent Usa, Inc.
- **Location:** Santa Clara, United States (Remote available)
- **Salary:** $100,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Bash Shell, C++ (Programming Language), Cloud Computing, Compilers, Computer Programming, Computer Engineering, Microarchitecture, Linux, Emulators, Python (Programming Language), CPU Design, Software Architecture, Quick EMUlator (QEMU), Reduced Instruction Set Computing, Software Engineering, Virtualization Technology, Information Technology
- **Published:** October 4, 2026
- **Apply:** https://startup.jobs/datacenter-agentic-ai-workload-performance-analysis-engineer-tenstorrent-company-10269404

## About the Role

* You have a strong background in CPU performance analysis, workload characterization, or computer architecture, with experience connecting software behavior to hardware performance.
 * You understand modern CPU microarchitecture, including superscalar pipelines, speculative execution, memory hierarchies, and vector/SIMD architectures.
 * You enjoy digging into complex workloads, using profiling and simulation data to identify bottlenecks and turn analysis into actionable recommendations.
 * You're comfortable working across hardware and software, from CPU microarchitecture and RTL to operating systems, compilers, runtimes, and applications.
 * You're a strong technical communicator who enjoys collaborating with architects, designers, and software engineers on complex performance problems., * PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field, with strong research or industry experience in workload characterization, benchmark development, performance analysis, or simulation.
 * Deep understanding of CPU architecture and RISC-V, including pipelines, speculative execution, vector/SIMD extensions, memory hierarchies, and performance tradeoffs.
 * Hands-on experience with performance analysis and simulation tools such as Linux perf, strace, QEMU, or CPU microarchitecture simulators.
 * Strong programming skills in C/C++, Python, Bash/Shell, and assembly or intrinsic programming, with experience working close to the hardware/software boundary.
 * Strong understanding of systems software, including operating systems, virtualization, compilers, runtimes, and GNU/RISC-V software ecosystems.

## Description

* How real-world datacenter and agentic AI workloads influence CPU microarchitecture and architectural decisions.
 * How to connect workload characterization and performance modeling to CPU design, RTL implementation, emulation, and silicon.
 * How hardware/software co-design can improve CPU throughput, scalability, and performance-per-watt efficiency.
 * How to analyze complex production workloads and reduce them into representative workloads and traces for architectural exploration.
 * How emerging RISC-V capabilities, cloud infrastructure, compiler technology, and AI software stacks are shaping the future of high-performance.