Sr. Software Engineer - Manufacturing Data & Test Infrastructure

Astera Labs•San Jose, CA
•$135,000 - $170,000

About The Position

Astera Labs is seeking a hands-on software engineer to own and improve internal platforms supporting manufacturing data, hardware test infrastructure, test automation, and failure analysis. The role combines software, data, infrastructure, and hardware operations, helping engineering and manufacturing teams work efficiently with reliable, actionable test data. The engineer will support systems that collect and organize test and manufacturing data from internal labs and manufacturing partners; maintain test automation and failure-analysis tools; improve service monitoring; and develop tools that help engineers identify root causes faster. The role includes taking ownership of existing systems, improving their reliability and maintainability, and extending them to support new products, test flows, and manufacturing sites. Strong data and test infrastructure helps engineering teams find failures faster, improve product quality, reduce manual investigation, and scale operations without bottlenecks. The role works closely with hardware, firmware, test, IT, and external partners to resolve system and data issues.

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a rated field.
  • At least 3 years building and operating backend systems, data systems, developer infrastructure, or internal platforms.
  • Strong Python skills, including experience with production services, scripts, libraries, or automation tools.
  • Experience with large-scale data processing and structured data pipelines.
  • Practical understanding of changing data formats, data quality challenges, and production data collection.
  • Experience with relational, analytical, or streaming data systems.
  • Experience supporting CI/CD systems, Git-based workflows, Linux environments, and containerized or cloud-based services.
  • Experience with monitoring and observability tools and the ability to balance operations with longer-term engineering improvements.

Nice To Haves

  • MS or PhD in Electrical Engineering or Computer Engineering.
  • Experience in semiconductors, hardware test, manufacturing test, or a similar engineering environment.
  • Familiarity with production test data, yield analysis, or manufacturing diagnostics.
  • Experience with public cloud services and secure external data exchange workflows.
  • Experience with infrastructure automation and configuration management tools.
  • Experience integrating collaboration and issue-tracking systems into automated workflows.
  • Experience working with external vendors, labs, or manufacturing partners.
  • Interest in AI-assisted failure analysis, debugging workflows, or internal knowledge tools.
  • Strong interest in building durable internal platforms that scale with engineering and manufacturing needs.

Responsibilities

  • Build, own, and improve data pipelines that collect, standardize, and organize manufacturing and test data.
  • Integrate data from internal and external sources, including lab test systems and manufacturing partners.
  • Improve data quality, pipeline reliability, handling of changing formats, and visibility into pipeline health.
  • Add support for new products, data sources, and manufacturing partners with minimal manual effort.
  • Make tools for accessing and analyzing data faster and easier to use.
  • Maintain and improve automation systems for hardware validation and production testing.
  • Keep build, test, and release workflows manageable, repeatable, and version controlled.
  • Operate and improve automated tools that process results, classify failures, and route issues to the right teams.
  • Reduce repetitive debugging through improved classification, dashboards, and internal tooling.
  • Operate services on Linux-based infrastructure using containers and cloud-hosted systems.
  • Support core platform services such as storage, scheduled jobs, and deployment automation.
  • Build and improve monitoring, alerting, and dashboards to detect issues early.
  • Improve day-to-day operations with runbooks, alert tuning, and safer rollout practices.
  • Support and extend shared telemetry and logging systems.
  • Build tools that help engineers explore logs, look up records, and diagnose failures faster.
  • Help build automated or AI-assisted debugging tools where they provide clear value.
  • Act as a technical point of contact for manufacturing data and test platform issues.
  • Work with hardware, firmware, test, IT, and external partners to resolve system and data issues.

Benefits

  • The role may be eligible for discretionary bonus, incentives, and benefits.
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