{"id":54588,"url":"https://alion.io/job/cadence-lead-application-engineer","title":"Lead Application Engineer","company":{"id":4351,"name":"Cadence Design Systems","domain":"cadence.com","url":"https://alion.io/company/cadence","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":108,"ghost_share":0,"stale_share":0.787,"repost_share":0,"time_to_fill_p50_days":57,"computed_at":"2026-11-15T07:52:55Z"}},"role":"Hardware","role_family":"Hardware","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Zhubei, Taiwan"],"countries":["TW"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":74000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":796},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Cadence Xcelium","optional":false},{"name":"Perl","optional":false},{"name":"Python","optional":false},{"name":"SystemVerilog","optional":false},{"name":"UVM","optional":false},{"name":"LLM","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-08-13T00:00:00Z","employer_posted_date":"2026-08-13","last_verified_at":"2026-11-15T01:50:12Z","board_verified":true,"closed_at":null,"days_open":94,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":93},"description":"At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.\nResponsibilities:\nEngage 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\nDevelop and optimize SystemVerilog/UVM-based verification environments for IP, subsystem, and SoC designs.\nDevelop reusable prompts, skills, agents, scripts, and AI-assisted workflows for customer applications.\nConduct technical evaluations, benchmarks, demonstrations, workshops, and customer training.\nTroubleshoot UVM, simulation, AI integration, and verification flow issues.\nCollaborate with R&D, Product Engineering, and support teams to address customer requirements and technical issues.\nDevelop technical collateral, AI use cases, reference flows, and best practices.\nQualifications:\nMS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.\nFive or more years of experience in digital design, functional verification, or EDA application engineering.\nStrong hands-on experience with SystemVerilog and UVM.\nExperience developing UVM environments, including agents, sequences, scoreboards, reference models, functional coverage, and register models.\nStrong understanding of constrained-random and coverage-driven verification methodologies.\nExperience integrating and debugging Verification IP in UVM-based environments.\nExperience with simulation, debug, coverage analysis, or low-power verification.\nExperience with Cadence tools such as Xcelium, Verisium, or VIP is a strong advantage.\nStrong scripting skills in Python, TCL, shell scripting, or Perl.\nAbility to translate verification challenges into practical and measurable AI-assisted solutions.\nStrong problem-solving, communication, presentation, and customer engagement skills.\nPreferred Qualifications:\nExperience architecting reusable UVM environments for complex SoC or subsystem verification.\nExperience applying AI or automation to testbench generation, sequence generation, coverage, debug, or regression analysis.\nFamiliarity with LLM APIs, prompt engineering, RAG, vector databases, agent-based workflows, MCP, or tool-calling frameworks.\nExperience deploying AI solutions in cloud-based or on-premises environments.\nKnowledge of CPU, interconnect, memory subsystem, low-power, or UPF verification.\nFamiliarity 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\nWe’re doing work that matters. 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