Principal ASIC Design Engineer

Reposted 22 Days Ago
Be an Early Applicant
2 Locations
In-Office
Expert/Leader
Hardware • Information Technology • Software
The Role
As a Principal ASIC Design Engineer, you will lead the ASIC design process from architecture to signoff, ensuring performance and quality targets are met while mentoring the engineering team.
Summary Generated by Built In

Positron.ai specializes in developing custom hardware systems to accelerate AI inference.  These inference systems offer significant performance and efficiency gains over traditional GPU-based systems, delivering advantages in both performance per dollar and performance per watt.  Positron exists to create the world's best AI inference systems.


Hiring Requisition: Principal ASIC Design Engineer


Position: Principal ASIC Design Engineer

Company: Positron.ai

Job Type: Full-time

Reports To: Director of ASIC Engineering

Location: (Onsite/Hybrid/Remote—your preference)


Company Overview

Positron.ai specializes in developing custom hardware systems to accelerate AI inference. Our systems deliver step-function improvements in performance per dollar and performance per watt versus traditional GPU-centric approaches. We exist to create the world’s best AI inference systems.

Position Overview

As a Principal ASIC Design Engineer, you will provide technical leadership across the full ASIC design lifecycle—owning the architecture, microarchitecture, RTL implementation, and front-end signoff of major subsystems for Positron.ai’s inference ASICs/SoCs. You will drive architectural decisions, establish best-in-class design methodologies, and ensure that all silicon meets aggressive PPA, schedule, and quality targets. This role is both highly technical and strategic: you will shape silicon architecture, mentor engineering teams, and represent ASIC design in cross-functional and executive discussions.

Key Responsibilities

Architecture & Technical Leadership:

  • Define system-level architecture and guide microarchitecture decisions for complex subsystems and cross-chip fabrics.
  • Lead technical scoping, partitioning, and tradeoff analyses across performance, power, and area.

RTL Design & Signoff Ownership:

  • Deliver production-quality, parameterized SystemVerilog RTL for critical IP and subsystems with robust power/clock intent and embedded assertions.
  • Drive front-end signoff activities (lint, CDC/RDC, DFT, synthesis/STA) and ensure readiness for back-end implementation.

High-Performance Interface & Memory Integration:

  • Architect and integrate advanced interconnects (AXI/CHI/ACE), DMA engines, coherency protocols, and high-speed memory interfaces (HBM/DDR) to meet demanding throughput and latency targets.
  • Coordinate with IP vendors and internal teams for seamless system integration.

Methodology, Standards & Innovation:

  • Define and maintain ASIC design methodology, coding standards, and reusable IP collateral across the organization.
  • Lead automation efforts (Python/Tcl/Make/CI) to improve team efficiency and design quality.

Cross-Functional Influence:

  • Collaborate closely with Architecture, Verification, PD, and Software to align requirements and resolve design issues quickly.
  • Present technical recommendations to leadership and influence product-level decisions.

Mentorship & Team Development:

  • Mentor and coach ASIC engineers across experience levels.
  • Lead technical reviews, fostering a culture of engineering excellence and continuous improvement.

Required Qualifications

  • BS/MS in EE/CE (or related) with 12+ years of ASIC/SoC RTL design experience, including technical leadership of large-scale, high-performance silicon projects.
  • Proven success in delivering blocks and subsystems from spec → architecture → microarchitecture → RTL → silicon with exceptional PPA results.
  • Expert SystemVerilog RTL skills and deep knowledge of clocking, resets, CDC/RDC, and protocol correctness.
  • Extensive experience with front-end design flows, EDA tools, and industry best practices.
  • Hands-on expertise in at least four of: HBM/DDR, PCIe/CXL, AMBA AXI/ACE/CHI, large-scale cache/memory hierarchies, high-throughput datapaths, NoC design.
  • Strong track record of influencing architecture and methodology decisions at the chip or system level.

Preferred Qualifications

  • Leadership experience in AI/ML accelerator design (matrix/vector engines, compression, NoC bandwidth planning).
  • Deep formal verification/SVA expertise for property checking and assertion-based design.
  • Low-power design leadership, including clock-/power-gating strategies, multi-voltage/multi-domain flows, and UPF/CPF.
  • Proven ability to define and roll out new ASIC design methodologies across teams.
  • Familiarity with RISC-V subsystems, coherence protocols, or advanced customer-owned tooling (COT) flows.

Why Join Us?

  • Shape the architecture and execution of groundbreaking AI inference hardware with a high-caliber, collaborative team.
  • Influence both the technology direction and the engineering culture of a rapidly growing company.
  • Competitive salary + equity, comprehensive benefits, and a flexible work environment.
  • Opportunities to drive innovation at the intersection of architecture, design, and product strategy.

Interested?

Apply with your resume and a brief note describing a subsystem or architecture you led from concept to tape-out, highlighting the PPA, methodology, and strategic tradeoffs you drove.


Top Skills

Ace
Amba
Axi
Chi
Ci
Cxl
Ddr
Hbm
Make
Pcie
Python
Systemverilog
Tcl
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The Company
HQ: Reno, NV
42 Employees
Year Founded: 2023

What We Do

Positron delivers vendor freedom and faster inference for both enterprises and research teams, by allowing them to use hardware and software explicitly designed from the ground up for generative and large language models (LLMs).

Through lower power usage and drastically lower total cost of ownership (TCO), Positron enables you to run popular open source LLMs to serve multiple users at high token rates and long context lengths. Positron is also designing its own ASIC to expand from inference and fine tuning to also support training and other parallel compute workloads.

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