About this Lead Application Engineer role at Cadence Design Systems
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
