Staff Software Engineer (Infrastructure)
Interested in defining how AI shapes the future of work? Cresta is on a mission to make every knowledge worker 100x as effective, 10x faster and 10x better. Cresta is focused on using AI to help the workforce, not replace them. Cresta uses our patented Expertise AI to uncover expert insights form every conversation and put those insights into action with real-time coaching during customer conversations.
We’re growing fast! Spun out of the Stanford AI lab and chaired by Google-X founder Sebastian Thrun, Cresta launched in 2020. Since then, we’ve grown revenue and our team by 300%! We’ve assembled a world-class team of AI and ML experts, go-to-market leaders, and top-tier investors and advisors including Andreessen Horowitz, Greylock Partners, and former AT&T CEO John Donovan. Our valued customers include brands like Intuit, Porsche, Adobe, and Dropbox and we have been recognized as a startup to watch by Business Insider, Forbes, and Gartner to name a few. We have huge ambitions and are looking for stellar candidates who have an entrepreneurial mindset and are excited to use cutting-edge AI to solve real-world business problems.
The team is responsible for designing, building and advancing our core infrastructure that allows the team to execute quickly, productively and securely. You will join a collaborative but highly autonomous working environment in which each member has a defined role with clear expectations, as well as the freedom to pursue projects they find interesting.
What You'll Do:
- Developer Toolchain. Partner with engineers to build dev tools that empower developer's workflow and deployment infrastructure.
- Ensure reliability of multi-cloud kubernetes clusters and pipelines.
- Metrics, logging, analytics and alerting for performance and security across all endpoints and applications.
- Infrastructure-as-code deployment tooling, supporting services on multiple cloud providers and on-premise virtualization.
- Automate operations and engineering. focus on automation so we can spend energy where it matters.
- Building machine learning infrastructure that enable AI team to train, test, and deploy on large-scale datasets.
What We Look For:
- 8+ years experience in DevOps, Site Reliability Engineering, Production Engineering or equivalent field.
- Proficiency with coding languages (e.g. Python)
- Deep familiarity with container-related security best practices.
- Experience working with Kubernetes clusterings.
- Experience with Terraform or CloudFormation (cloud orchestration)
- Experience working with AWS
- Exposure to infrastructure-as-code frameworks.
- Experience on CI/CD and feature gating systems.
- Fluency in Linux operations and configurations.