Tech Lead Automation Engineer

Astera Labs•San Jose, CA

8d•$135,000 - $170,000

About The Position

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 www.asteralabs.com . The role We are seeking a hands-on Tech Lead Automation Engineer with a passion for infrastructure and SG&A automation to lead the development of the internal platforms that let the rest of the company move faster. You'll take ownership of the systems that automate access, tracking, and administrative workflows across engineering and the business — deciding what gets built, building a meaningful share of it yourself, and setting the technical direction as that footprint grows. This is a builder's role, not a purely architectural one: you'll be writing code, designing schemas, and shipping features personally, using AI coding platforms like Claude Code, Cursor, and GitHub Copilot as core tools in your daily work.

Requirements

BS/MS in Computer Science with 7+ years of professional software engineering experience.
Demonstrated ownership of a production web application end-to-end: backend (Python; FastAPI or similar), relational database design (PostgreSQL, SQL, schema migrations), and frontend work.
Experience integrating with enterprise SaaS APIs (e.g. Atlassian suite, Microsoft 365, GitHub/Bitbucket) and cloud infrastructure APIs (compute/storage, job schedulers).
Working knowledge of identity and access management — RBAC, SSO/OAuth2, and group provisioning via a directory service (LDAP or equivalent).
Experience designing systems of record or inventory/asset-tracking tools, and the dashboards that surface their data to different audiences.
Fluency with AI-assisted coding tools (Claude Code, Cursor, GitHub Copilot) as part of a daily development workflow.
A strong bias toward automating manual, cross-functional processes, and comfort scoping those flows directly with non-technical stakeholders (IT, HR, Finance).
A track record as a hands-on technical lead — someone who owns architecture decisions and personally builds a meaningful share of the system, not just one who delegates.

Nice To Haves

Exposure to licensing, entitlement, or lifecycle-tracking systems (software licenses, IP/asset lifecycle, or similar compliance-adjacent tracking) is a strong plus.

Responsibilities

Take technical ownership of our internal automation platforms end-to-end — architecture, data model, background sync/scheduling, and roadmap.
Design and ship full-stack features: backend services, role-based access control, approval workflows, and frontend UI.
Maintain and extend integrations with the external systems these platforms depend on — SaaS tools, cloud infrastructure, and internal directory/identity services.
Design and build new operational systems from the ground up in response to emerging business needs, including systems of record for tracking assets and entitlements, and dashboards that give teams visibility into usage, cost, and status.
Grow existing tooling in these areas from functional-but-narrow into fuller self-service products.
Partner with IT, HR, and Finance-adjacent stakeholders to automate SG&A workflows — onboarding/offboarding, approval routing, audit logging, and access reviews — while those teams continue to own the underlying policy.
Build identity and access integrations (SSO/OAuth2) and RBAC models that satisfy audit requirements without slowing teams down.
Own database schema evolution and maintain automated test coverage as the codebase and its scope grow.
Use AI coding platforms as a daily force multiplier for scaffolding, testing, and delivery speed.
Set and enforce engineering standards (separation of concerns, commit discipline, logging) as the codebase scales beyond a single owner.