Senior Principal Automation Engineer

Astera Labs•San Jose, CA

3d•$205,000 - $260,000

About The Position

Astera Labs is seeking a visionary Senior Principal Automation Engineer with over two decades of experience architecting, modernizing, and scaling cloud-native infrastructure for semiconductor design workflows. This role will be the technical authority on CI/CD pipelines, cloud HPC infrastructure, and automated performance and validation loops for both front-end and back-end semiconductor design processes. The position also involves automating business functions supporting the design organization, such as HR, Legal, and Finance, focusing on areas like the employee lifecycle. The goal is to transform these workflows into ultra-reliable, cost-efficient, automated ecosystems using modern software engineering practices and AI-driven optimization, with a focus on AI coding platforms like Claude Code, Cursor, and GitHub Copilot.

Requirements

BS/MS/Ph.D. in Computer Science, Electrical Engineering, Software Engineering, or a related technical discipline.
20+ years of progressive technical experience.
At least 10+ years specializing in CAD infrastructure, cloud HPC, or build/release automation for complex engineering environments.
Deep hands-on expertise running HPC/EDA workloads natively in the cloud (AWS preferred), including cost optimization.
Working knowledge of both front-end and back-end semiconductor design flows.
Data engineering experience building and operating data lakes (e.g., S3, Glue, Athena, Prometheus, Redshift, Snowflake, or Spark) and delivering role-tailored dashboards/insights (e.g., Grafana, Tableau).
Expert command of enterprise CI/CD orchestration tools (Jenkins, GitHub Actions).
Advanced proficiency in core automation languages (Python, Shell/Bash, Tcl) and Linux/Unix system administration.
Demonstrated expertise using AI coding platforms (Claude Code, Cursor, GitHub Copilot) as core development tools.
Proven track record of defining corporate-wide automation visions that measurably elevate engineering velocity, cost efficiency, and system reliability.
Experience contributing to business-process automation outside engineering (HR, Legal, Finance, or IT service management), including employee lifecycle and identity/access provisioning.
Demonstrated ability to translate non-technical stakeholder processes into durable automated flows.
Ability to build automation that satisfies audit and compliance requirements (SOX controls, access reviews, data privacy) without slowing the business down.

Nice To Haves

Experience building and rebuilding CI/CD and HPC systems across multiple technology generations without relying on on-prem compute.
Fluency in thinking about cost-per-simulation and cloud spend alongside pipeline throughput.
Understanding of both ends of the semiconductor design flow to identify inefficiencies.
Experience building data platforms and understanding the value of a data lake for different roles.
Fluent use of AI coding tools as a force multiplier at scale.
Comfortable whiteboarding business processes with HR, Legal, and Finance partners.
Mentoring teams and setting technical direction across organizations.
Ability to speak credibly to both hands-on engineers and executive leadership.

Responsibilities

Architect and optimize CI/CD pipelines and shared automation libraries for large-scale ASIC and SoC development on cloud infrastructure.
Optimize front-end (RTL, simulation, verification) and back-end (physical design, place-and-route, timing closure) semiconductor workflows for engineering and cloud cost efficiency.
Own cloud HPC compute strategy, including auto-scaling, job scheduling, and license-aware scheduling, to maximize throughput and reduce cost-per-run.
Provision and manage cloud compute clusters, virtual runners, artifact repositories, and secure credential environments using Infrastructure as Code.
Design and build a centralized data lake for HPC, CI/CD, License, and design-tool telemetry data.
Partner with stakeholders to define role-specific insight views and dashboards based on the data lake.
Evaluate and deploy AI-assisted telemetry for regression triage, automated failure analysis, root-cause debugging, and pipeline/cost forecasting.
Develop automation frameworks to integrate source control systems, code review platforms, and specialized CAD/EDA tools.
Leverage AI coding platforms to accelerate development of automation scripts, tooling, and infrastructure code.
Participate in automation initiatives with HR, Legal, and Finance, applying engineering rigor to manual processes.
Contribute to end-to-end employee lifecycle flows (onboarding to offboarding), including offer-to-hire, identity provisioning, tool entitlement, environment setup, and deprovisioning.
Support Legal workflow automation, including NDA/contract intake, review routing, e-signature, IP disclosure, and obligation tracking.
Support Finance workflow automation, including purchase requisitions, invoice approvals, chargeback/showback, and spend forecasting.
Integrate enterprise systems of record with the engineering automation stack via APIs and workflow tools.
Build compliance and control into flows, including approval gates, segregation of duties, audit trails, and data privacy requirements.
Act as principal advisor on cloud infrastructure investment, cost strategy, and long-term automation roadmap.
Partner with various teams to build resilient, standardized, cost-transparent engineering environments.