Senior Principal Automation Engineer

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at [](http://www.asteralabs.com/). The role We are seeking a visionary Senior Principal Automation Engineer with over two decades of experience architecting, modernizing, and scaling the cloud-native infrastructure that powers semiconductor design workflows. This role will be the definitive technical authority on CI/CD pipelines, cloud HPC infrastructure, and automated performance and validation loops across both front-end (RTL, simulation, verification) and back-end (physical design, place-and-route, timing closure) semiconductor flows. Beyond engineering, this role also participates in automation work across the business functions that support the design organization — HR, Legal, and Finance — contributing to flows such as the end-to-end employee lifecycle from onboarding to offboarding, where those teams own the process and this role brings the automation and engineering rigor. You will lead the transformation of these workflows into ultra-reliable, cost-efficient, automated ecosystems — incorporating modern software engineering practices and AI-driven workflow optimization. You'll use AI coding platforms like Claude Code, Cursor, and GitHub Copilot as core tools in your daily engineering work. What you'll do Cloud HPC & Workflow Optimization · Architect and optimize CI/CD pipelines, and shared automation libraries supporting large-scale ASIC and SoC development, entirely on cloud infrastructure. · Optimize front-end (RTL, simulation, verification) and back-end (physical design, place-and-route, timing closure) semiconductor workflows for both engineering efficiency and cloud cost efficiency. · Own cloud HPC compute strategy — auto-scaling, job scheduling, and license-aware scheduling — to maximize throughput while continuously driving down cost-per-run. · Provision and manage cloud compute clusters, virtual runners, artifact repositories, and secure credential environments using modern Infrastructure as Code. Data & Insights · Design and build a centralized data lake aggregating all HPC, CI/CD, License and design-tool telemetry data across the organization. · Partner with design, verification, physical design and management stakeholders to define role-specific insight views (e.g., engineer-level regression health, manager-level throughput/cost dashboards, executive-level capacity and spend trends) built on top of the data lake. · Evaluate and deploy AI-assisted telemetry for regression triage, automated failure analysis, root-cause debugging, and pipeline/cost forecasting. Automation & Tool Integration · Develop automation frameworks that seamlessly integrate source control systems, code review platforms (Git, Bitbucket), and specialized CAD/EDA tools. · Leverage AI coding platforms (Claude Code, Cursor, GitHub Copilot) to accelerate development of automation scripts, tooling, and infrastructure code. Cross-Functional Automation (HR, Legal, Finance) · Participate in automation initiatives with HR, Legal, and Finance, bringing engineering rigor to manual, hand-off-heavy processes while those teams own the underlying policies and processes. · Contribute to end-to-end employee lifecycle flows from onboarding to off-boarding: offer-to-hire handoff, identity and access provisioning, EDA/software license and tool entitlement, hardware and cloud environment setup, role and org transfers, and fully audited deprovisioning on exit. · Support Legal workflow automation — NDA and contract intake, review routing and approvals, e-signature, IP disclosure and open-source review requests, and obligation tracking with searchable records. · Support Finance workflow automation — purchase requisition and invoice approvals, license and cloud-spend chargeback/showback by team, budget-versus-actual reporting, and spend forecasting driven off the same telemetry data lake. · Help integrate enterprise systems of record with the engineering automation stack through APIs, event-driven triggers, and workflow/iPaaS tooling. · Work with process owners to build compliance and control into these flows — approval gates, segregation of duties, audit trails, access reviews, and data-retention and privacy requirements (SOX, GDPR/CCPA). Leadership · Act as principal advisor on cloud infrastructure investment, cost strategy, and long-term automation roadmap. · Partner with design, verification, IT, data, HR, Legal, and Finance teams to build resilient, standardized, cost-transparent engineering environments. What we're looking for · BS/MS/Ph.D. in Computer Science, Electrical Engineering, Software Engineering, or a related technical discipline. · 20+ years of progressive technical experience, including 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 well enough to identify workflow and cost inefficiencies across the full ASIC/SoC development cycle. · 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 (onboarding through offboarding) and identity/access provisioning. · Demonstrated ability to translate non-technical stakeholder processes into durable automated flows, and to build automation that satisfies audit and compliance requirements (SOX controls, access reviews, data privacy) without slowing the business down. What strong candidates often look like They have spent a career deep in cloud-native CAD/EDA infrastructure, having built and rebuilt CI/CD and HPC systems across multiple technology generations without ever relying on on-prem compute. They think as fluently about cost-per-simulation and cloud spend as they do about pipeline throughput, and they know both ends of the semiconductor design flow well enough to find inefficiencies in each. They've built data platforms before, not just pipelines — and understand that a data lake is only valuable when different roles can see the insights that matter to them. They use AI coding tools fluently, not as a novelty, but as a force multiplier at scale. They are equally comfortable whiteboarding a hiring-to-offboarding process with HR, Legal, and Finance partners as they are debugging a regression pipeline — because they see both as the same problem: manual handoffs that should be code. They've mentored teams, set technical direction across organizations, and can speak credibly to both hands-on engineers and executive leadership. Why this role is interesting This is a rare principal-level mandate to optimize cloud-native CAD infrastructure, just a clean cloud-first foundation to optimize for speed and cost simultaneously. You'll shape how front-end and back-end semiconductor teams work, build the data lake that turns every HPC run into an organizational insight, and set the technical vision others build against — all using the most modern development tools available. The charter is unusually broad: the same platform mindset applies to how a new engineer becomes productive on day one, how a contract moves through Legal, and how cloud and license spend gets attributed back to the teams driving it — so the automation you build is felt across the whole company, not just the design flow. Salary range is $205,000 to $260,000 depending on experience, level, and business need. This role may be eligible for discretionary bonus, incentives and benefits. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.