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 We’re doing work that matters. Help us solve what others can’t.