Software Development Engineer in Test - AI
Delos Data
hybridmidpermanentqabackend Palo Alto, CA Yesterday via LinkedIn
140,000 - 200,000 USD/annual
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PythonTest AutomationSDETDistributed SystemsStress TestingDockerKubernetesCI/CDTelemetryAI Infrastructure
About the role
Role Overview
Delos Data is hiring a Software Development Engineer in Test (SDET) – AI to ensure the reliability and performance of its core AI infrastructure. You will build automation and stress-testing suites that help “break and harden” distributed AI systems across hardware and software boundaries.
Responsibilities
- Design, develop, and maintain automated testing frameworks from the ground up for distributed AI training and inference workloads.
- Create complex test plans beyond unit tests, including end-to-end integration, stress testing, and hardware-software boundary validation.
- Collaborate with System Engineers to debug deep issues in distributed clusters using telemetry and profiling to identify bottlenecks.
Required Skills / Qualifications
- Strong proficiency in Python for automation and orchestration.
- Experience building/extending test automation frameworks for complex back-end systems.
- Ability to troubleshoot automated test failures in large-scale distributed systems and identify root causes.
- Experience with containerization (Docker/Kubernetes) and modern CI/CD tools (GitHub Actions, GitLab CI, or Jenkins).
- Education: Bachelor’s or Master’s in Computer Engineering, Computer Science, or related field.
Desired Skills
- Experience with Kubernetes and/or Terraform and/or Ansible for managing test-bed environments.
- Experience testing high-performance networking protocols or distributed file systems.
- Experience testing software that interacts directly with drivers or firmware.
Compensation
- Target base salary: $140,000–$200,000/year plus meaningful equity, benefits, and 401(k).
About Delos Data
Delos Data is a stealth-mode startup building foundational technology for large-scale AI data center clusters. The company focuses on performance, scalability, and resiliency, working across distributed systems and AI infrastructure with a mix of remote and on-site locations in the U.S. and Canada.
Scraped 4/1/2026