Sr. Software Engineer - Manufacturing Data & Test Infrastructure

Description

The company provides rack-scale AI infrastructure built on purpose-built connectivity products, working with hyperscalers and ecosystem partners.

Its connectivity platform combines CXL, Ethernet, NVLink, PCIe and UALink semiconductor technologies with its COSMOS software suite to build flexible systems for scale-up and scale-out connectivity.

A separate custom connectivity business builds tailored architectures for customers whose infrastructure needs go beyond the standard portfolio.

The team is hiring a hands-on senior software engineer to own and improve the internal platforms for manufacturing data, hardware test infrastructure, test automation and failure analysis.

The role combines software, data, infrastructure and hardware operations, and helps engineering and manufacturing teams act quickly on test data they can trust.

You will keep existing systems reliable and easy to maintain while extending them to new products, test flows and manufacturing sites.

Strong data and test infrastructure lets engineers find failures sooner, raise product quality, cut manual investigation and grow operations without creating bottlenecks.

Responsibilities

• Manufacturing and Test Data Platforms:
• Build, own and improve pipelines that gather, standardize and organize manufacturing and test data.
• Combine data from internal and external sources such as lab test systems and manufacturing partners.
• Raise data quality and pipeline reliability, handle shifting formats, and make pipeline health visible.
• Onboard new products, data sources and manufacturing partners with little manual work.
• Make the tools engineers use to query and analyze data quicker and simpler to use.
• Test Automation and Failure Analysis
• Maintain and improve automation that supports hardware validation and production testing.
• Keep build, test and release workflows manageable, repeatable and under version control.
• Run and enhance automated tools that process results, classify failures and send issues to the right teams.
• Cut repeated debugging with better classification, dashboards and internal tooling.
• Infrastructure, Reliability and Monitoring
• Run services on Linux infrastructure using containers and cloud-hosted systems.
• Support core platform services including storage, scheduled jobs and deployment automation.
• Build and improve monitoring, alerting and dashboards so problems surface early.
• Improve daily operations through runbooks, alert tuning and safer rollout practices.
• Internal Tools and Cross-Functional Support
• Support and extend shared telemetry and logging systems.
• Build tools that help engineers search logs, look up records and diagnose failures faster.
• Help build automated or AI-assisted debugging tools where they clearly add value.
• Serve as the technical contact for issues involving manufacturing data and test platforms.
• Work with hardware, firmware, test, IT and external partners to resolve system and data problems.
• Success in the role means new manufacturing and test data sources arrive quickly and reliably, engineers reach trusted data without specialist help, and test automation and failure-analysis systems stay stable and understandable.
• Operational issues are caught early through good dashboards and alerts, and documentation and tooling are strong enough for the whole team to share ownership.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering or a rated field.
• 3+ years building and running backend, data, developer infrastructure or internal platform systems.
• Strong Python skills across production services, scripts, libraries and automation tools.
• Experience with large-scale data processing and structured data pipelines.
• Practical grasp of changing data formats, data quality issues and production data collection.
• Experience with relational, analytical or streaming data systems.
• Experience supporting CI/CD systems, Git workflows, Linux environments and containerized or cloud services.
• Experience with monitoring and observability tools, and the judgment to balance operations work with longer-term engineering improvements.
• Preferred: MS or PhD in Electrical Engineering or Computer Engineering.
• Preferred: experience in semiconductors, hardware test, manufacturing test or a similar engineering setting.
• Preferred: familiarity with production test data, yield analysis or manufacturing diagnostics.
• Preferred: experience with public cloud services and secure external data exchange workflows.
• Preferred: experience with infrastructure automation and configuration management tools.
• Preferred: experience connecting collaboration and issue-tracking systems to automated workflows.
• Preferred: experience working with external vendors, labs or manufacturing partners.
• Preferred: interest in AI-assisted failure analysis, debugging workflows or internal knowledge tools.
• Preferred: strong interest in building durable internal platforms that scale with engineering and manufacturing needs.

Conditions

Salary range is $135,000 to $170,000, depending on experience, level and business need.

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

The company encourages applications from people with relevant experience of all backgrounds, including people of color, LGBTQ+ and non-binary people, veterans, parents and people with disabilities.

Benefits

• May be eligible for a discretionary bonus and incentives.