Member of Technical Staff - Design Verification

About Architect

Architect is a frontier AI lab for chip design. We build AI models and tools for on-demand custom ASICs at scale. Our goal is to co-design custom ASICs alongside evolving ML workloads, and enable a new era of domain-specific chips that unlock capabilities impossible with current hardware paradigms. Born out of Stanford Research, our team blends AI with Silicon with a founding team from Anthropic, Google DeepMind, Meta SuperIntelligence, xAI, Apple and Intel.

What You'll Do

As a Founding Member of the Technical Staff on the Design Verification team at Architect, you'll own the verification strategy behind AI-generated designs taping out on leading foundries. You'll work at the intersection of rigorous hardware verification and AI-driven design automation.

• Review AI-driven test plan, and validation strategy for internal and external SoC projects.

• Provide domain-specific expertise to our AI/ML teams, including architectural and microarchitectural checks, validation modularity, checkers, coverage models, and interface protocols — helping encode DV best practices into our AI-driven flows.

• Independently define, drive, and coordinate validation, verification, and integration flows across multiple IPs, including checkpoints and collateral handoffs.

• Collaborate with architecture, design, and AI/ML leads to generate simulation- and emulation-ready collateral that scales across projects.

• Track emerging trends in semiconductor verification and AI-driven design automation to keep our methodology cutting-edge in quality, scalability, and throughput.

What We'd Like to See

Qualifications & Skills:

• Degree: Bachelor's, Master's, or PhD in Electrical Engineering, Computer Engineering, or a closely related field.

• Tapeout Experience: 5+ years (10+ preferred) working on advanced-node tapeouts at top chip companies or fast-moving silicon startups. End-to-end silicon delivery is a strong plus.

• Verification Expertise: Deep expertise in verification/validation, emulation, and architectural and system-level verification of industry-standard IPs. Proven track record defining microarchitectural checkers and monitors, modeling IP and SoC validation platforms, and developing modular, reusable validation collateral.

• Coding: Strong skills in SystemVerilog, UVM, and C/C++ for test environments. Python strongly preferred.

• Subsystem Depth: Hands-on verification experience in at least one of the following areas:

  • ARM/AMBA protocols (APB, AHB, AXI, and ideally ACE for coherent CPU interfaces)

  • CPU subsystems — boot, interrupts, debug, coherency

  • Memory controllers and PHY — LPDDR/DDR interfaces, controller-level verification

  • On-chip interconnect / NoC — routing, arbitration, QoS, bandwidth

  • NPU / ML accelerator cores — datapath, scratchpad memory, DMA engines

  • Security IPs and/or working with secure enclaves

• Methodology: Hands-on experience with simulation and emulation flows and methodologies. Experience mapping IP and SoC designs to FPGA prototypes for fast functional verification.

• Execution: Excellent problem-solving, collaboration, and communication skills with strong attention to detail. Ability to work independently and drive cross-functional alignment.

• Leadership: Ability and desire to lead the DV function over time as the team scales.

Bonus:

• SoC-level DV experience — bringing up full systems with memory controller + PHY + CPU connectivity, validating top-level integration.

• Deep experience with AMBA protocols, specifically ACE for coherent CPU-memory access.

• FPGA prototyping experience (ideally Xilinx Vivado/Vitis).

• Verification experience spanning multiple of: interconnects, CPU subsystems, ARM AMBA, memory controllers, NPUs.

• Tapeout experience at frontier AI chip startups (MatX, Groq, Cerebras, d-Matrix, etc.) or tier-1 silicon companies (Apple, NVIDIA, Google, Qualcomm, Broadcom, AMD).

What We Offer

• Competitive salary and meaningful equity stake

• Fast-paced startup with autonomy and visible impact

• Cutting-edge challenges at the intersection of AI and silicon design