Emulation DV Engineer — SoC/IP Verification Architect

River AI Inc.; Palo Alto, Austin (CA, TX); On-site; USD 200,000 - 420,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation assistance

Health benefits

Unlimited PTO

Job summary

River AI is seeking an emulation-focused design verification engineer to drive IP/SoC verification on emulation platforms. You will translate architectural definitions into emulation workloads and collaborate with DV owners to achieve emulation signoff as part of overall verification closure.

You will also develop models and infrastructure to support this work, including automation and scripting in Python, Tcl, and Bash, ensuring high throughput and traceability across the verification stack.

Qualifications

• Bachelor’s degree in electrical/computer engineering, CS, or related field.
• 5+ years of industry experience in verification.
• Experience with emulation or acceleration platforms and DV.
• Strong understanding of verification planning and closure.
• Experience verifying complex IP/SoCs and translating DV goals to workloads.

Responsibilities

• Define emulation strategy based on tests, fidelity, and debug needs.
• Build and maintain models and components for emulation workflows.
• Develop platform bring-up, compile, mapping, runtime, and debug flows.
• Triage failures using traces, waveforms, and diagnostics; collaborate with RTL/DV teams.
• Develop agentic workflows and automation to improve throughput and traceability.

Skills

SystemVerilog

C/C++

Python

Tcl/Bash scripting

Debugging

Education

Bachelor’s degree in Electrical/Computer Engineering or CS

Tools

Cadence Palladium/Protium

Synopsys ZeBu/HAPS

Testbench & Workload Development

Job description

River AI is seeking an emulation-focused design verification engineer to drive IP/SoC verification on emulation platforms. You will translate architectural definitions into emulation workloads and collaborate with DV owners to achieve emulation signoff as part of overall verification closure.

You will also develop models and infrastructure to support this work, including automation and scripting in Python, Tcl, and Bash, ensuring high throughput and traceability across the verification stack.