# Physical Design Implementation and Signoff Methodology Lead & Architect at Altera

- Company: Altera
- What the company does: Backed by a16z.
- Company website: https://www.altera.com
- Type: Startups
- Level: Senior
- Location: San Jose, California, United States
- Work setup: On-site
- Pay: $232K to $341K base salary per year (USD)
- Posted: 2026-09-22
- Apply by: 2026-11-06
- Apply: https://altera.wd1.myworkdayjobs.com/en-US/Altera/job/San-Jose-California-United-States/Physical-Design-Implementation-and-Signoff-Methodology-Lead---Architect_R03217
- Page: https://www.1752.vc/careers/jobs/altera-physical-design-implementation-and-signoff-methodology-lead-and-architect/

## About the role

We are looking for a Physical Design Implementation & Signoff Methodology Lead & Architect to own and reinvent the implementation and signoff methodology that underpins every tapeout at Altera. This is a senior individual-contributor role for an engineer who thinks like an architect: someone who doesn't just close implementation and signoff on a single block, but builds the flows, standards, and quality gates — supercharged with an AI/ML-driven mindset — that let every design team close faster, with higher quality...

## What they're looking for

- Deep, hands-on expertise in physical design implementation and signoff methodology, including electromigration and IR-drop (EMIR) analysis
- Strong command of timing signoff (STA) and power signoff flows, and the industry standards that govern them
- A demonstrated track record of architecting and deploying PD implementation and signoff methodologies across multiple tapeouts and process technology nodes
- Hands-on proficiency with industry-standard place-and-route, EMIR, STA, and power signoff tools (e.g., Ansys RedHawk-SC, Synopsys PrimeTime/PrimePower/Fusion Compiler, Cadence Innovus/Voltus/Tempus, or equivalent)
- Excellent cross-functional collaboration and communication skills, with the ability to influence design methodology across multiple teams and sites
- Scripting and automation proficiency (Python, Tcl) sufficient to build methodology infrastructure and integrate ML pipelines directly, not only to script around flows others have built