Agrani Labs

Micro-Architect / RTL Designer – Compute Core

Compute Core Team · 5-15 years

Posted
9 Jul 2026
Last verified at source
2 days ago
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Agrani Labs is building a high-performance AI accelerator designed for the next generation of intelligent computing. We’re looking for talented and driven Micro-Architects, RTL Designers, and RTL Validation Engineers to join our Compute Core Team. You’ll work alongside a world-class engineering team with deep expertise in advanced processor and accelerator design. You’ll play a key role in architecting and implementing the compute core of a cutting-edge AI accelerator. This includes working across areas such as front-end design, execution clusters, memory pipelines, math engines, caches, and interconnects — while driving aggressive optimization for power, performance, and area (PPA). B.Tech, Master’s, or Ph.D. in Electrical Engineering, Computer Science, or related fields, with 5–15 years of industry experience Strong understanding of CPU, GPU, or XPU architecture fundamentals Hands-on expertise in micro-architecture and RTL development across one or more domains such as front-end pipelines, execution clusters, memory subsystems, math units, or cache architectures Strong experience with RTL verification/debug methodologies and performance validation Proven track record of PPA optimization and design tradeoff analysis Experience with modern ASIC design and validation flows is preferred Familiarity with AI/ML workloads and their hardware execution characteristics is a plus Be part of a world-class engineering team with an open and collaborative work culture Get a unique opportunity to work on grounds-up hardware and software development at scale Connect the dots across the entire system and stack, from Torch to transistors Work at an AI first company, and use AI innovatively to transform the way hardware and software are built Get practically unlimited access to top models from OpenAI, Anthropic and Gemini models and more Interested in this role? Submit your application below