Software Development Engineer in Test - AI
About us:
We are a stealth-mode startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. We are backed by top-tier VC firms and notable angel investors.
The company is led by experienced builders and operators who have founded companies, taken them to scale, and exited successfully. We work with a strong sense of unity and shared responsibility, and we expect trust, integrity, and respect in how we collaborate and make decisions. We hold ourselves accountable to one another and to the quality of the work we deliver.
Headquartered in Silicon Valley, we operate across a mix of remote and on-site locations in the U.S. and Canada. We aim to create an environment where people are treated fairly, supported in their growth, and are empowered to do meaningful work alongside others who take the craft seriously.
We are looking for:
We are looking for a Software Development Engineer in Test (SDET) to ensure the reliability and performance of our core AI infrastructure. In this role, you are an engineer who builds sophisticated automation frameworks and stress-testing suites to break and then harden our system.
You will be responsible for validating the intersection of distributed systems, GPU kernels, and AI frameworks. You will build a scalable foundation of trust in our code, ensuring that our performance-critical primitives work every time, at any scale.
Key Responsibilities:
Design, develop, and maintain a robust automated testing framework from the ground up that supports distributed AI training and inference workloads.
Develop complex test plans that go beyond unit tests, focusing on end-to-end system integration, stress testing, and hardware-software boundary conditions.
Partner closely with System Engineers to debug deep-seated issues in distributed clusters, using telemetry and profiling tools to identify bottlenecks.
Required Skills and Qualifications:
Strong proficiency in Python (for automation and orchestration).
Proven experience building or extending test automation frameworks for complex back-end systems.
Proven ability to troubleshoot automated test failures within complex large-scale distributed systems, and identify root causes.
Experience with containerization (Docker/Kubernetes) and modern CI/CD tools (GitHub Actions, GitLab CI, or Jenkins).
Desired Skills:
Experience with Kubernetes or Terraform 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.
Education:
Bachelor's or Master's degree in Computer Engineering, Computer Science, or a related field.
Compensation:
Target base salary for this role is $140,000 - $200,000 per year + meaningful equity + benefits + 401k. Our salary ranges are determined by role, level, experience, and location.
Agency Note:
We do not accept resumes from agencies or search firms. Please do not forward candidate profiles through our careers page, email, LinkedIn messages, or directly to company employees. Any resumes submitted will be deemed the property of the company, and no fees will be paid in the event the candidate is hired.
Top Skills
What We Do
Interconnect Built for AI Inference
Why Work With Us
We are a mixture of software, system, and silicon experts using AI every day to deliver the world's most capable and responsive intelligence. We start from the workload. Scaling inference is less about brute force and more about how compute is distributed and memory is interc
