Run:AI is bridging the gap between data science and computing infrastructure by creating a high-performance compute virtualization layer for deep learning, speeding the training of neural network models and enabling the development of large AI models. By abstracting workloads from underlying infrastructure, Run:AI creates a shared pool of resources that can be dynamically provisioned for full utilization of expensive GPU compute.
Job Description
Run:AI is seeking a highly motivated and skilled Automation Engineer with infra orientation to join our team. The person will be responsible for designing, developing, and implementing automation infrastructure solutions to improve production efficiency and reliability, as well as reduce release cycle time.
Responsibilities
- Become an expert in Run:AI Automation project and tools and master their interaction with our many microservices and ci workflows
- Develop and improve testing infrastructure for, and alongside, automation engineers, and push to maintain high stability and success rate of tests across multiple complex environments.
- help increase success and coverage visibility for stakeholders in the R&D.
- Be a primary point of contact for quality and release related matters for stakeholders.
- Investigate, analyze, and report failures while working closely with developers and TLs.
- Take a major role in enabling and maintaining a high pace, high quality release process.
Qualifications
What we are looking for in the candidate is first and foremost a strong sense of responsibility, extreme ownership and attention to details. The employee will need the ability to work both independently and in a team environment is required to have strong communication skills.
The following knowledge and skills are also required
- 5+ years experience in automating test scenarios. (JS - advantage).
- Experience with maintaining stable e2e suites and assisting in the release cycle.
- Experience with CI/CD tools (Github Actions or similar).
- Experience with building infrastructure for automation projects
- Experience with containers and cloud, preferably Docker & Kubernetes.
- Strong background in Quality Assurance.
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