Lead Application Engineer

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Responsibilities:

• Engage with customers to understand verification challenges and identify suitable AI-assisted verification use cases. - UVM testbench and component generation - Test and sequence generation - VIP integration and configuration - Assertion and functional coverage generation - Simulation failure triage and root-cause analysis - Log and waveform analysis - Verification flow automation

• Develop and optimize SystemVerilog/UVM-based verification environments for IP, subsystem, and SoC designs.

• Develop reusable prompts, skills, agents, scripts, and AI-assisted workflows for customer applications.

• Conduct technical evaluations, benchmarks, demonstrations, workshops, and customer training.

• Troubleshoot UVM, simulation, AI integration, and verification flow issues.

• Collaborate with R&D, Product Engineering, and support teams to address customer requirements and technical issues.

• Develop technical collateral, AI use cases, reference flows, and best practices.

Qualifications:

• MS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.

• Five or more years of experience in digital design, functional verification, or EDA application engineering.

• Strong hands-on experience with SystemVerilog and UVM.

• Experience developing UVM environments, including agents, sequences, scoreboards, reference models, functional coverage, and register models.

• Strong understanding of constrained-random and coverage-driven verification methodologies.

• Experience integrating and debugging Verification IP in UVM-based environments.

• Experience with simulation, debug, coverage analysis, or low-power verification.

• Experience with Cadence tools such as Xcelium, Verisium, or VIP is a strong advantage.

• Strong scripting skills in Python, TCL, shell scripting, or Perl.

• Ability to translate verification challenges into practical and measurable AI-assisted solutions.

• Strong problem-solving, communication, presentation, and customer engagement skills.

Preferred Qualifications:

• Experience architecting reusable UVM environments for complex SoC or subsystem verification.

• Experience applying AI or automation to testbench generation, sequence generation, coverage, debug, or regression analysis.

• Familiarity with LLM APIs, prompt engineering, RAG, vector databases, agent-based workflows, MCP, or tool-calling frameworks.

• Experience deploying AI solutions in cloud-based or on-premises environments.

• Knowledge of CPU, interconnect, memory subsystem, low-power, or UPF verification.

• Familiarity with one or more protocols, including: - AMBA CHI, AXI, or AHB - USB or USB4 - LPDDR or HBM - UFS, UniPro, or M-PHY - PCI Express - DisplayPort or eMMC

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