Software Engineer, Infrastructure
AI summary of the role
Infrastructure engineer at an early-stage AI-for-physical-sciences startup in San Francisco, owning customer-hosted cloud deployments, incident response, and internal tooling.
What you’ll do
- Architect and own complex customer-hosted cloud deployments that run scalably and reliably across diverse customer environments.
- Triage, debug, and resolve high-severity issues end-to-end, building automated safeguards and observability to prevent regressions.
- Design fully automated, repeatable deployment pipelines with deep observability to surface edge cases before production.
- Drive developer velocity and build internal tooling to help the engineering team ship fast without sacrificing reliability or security.
What you’ll bring
- Operating production Kubernetes and cloud infrastructure.
- Delivering on-prem or customer-hosted software.
- Strong Linux, networking and infrastructure-as-code fundamentals.
- Independently owning incidents and communicating with customers.
Technologies
Kubernetes · AWS · Terraform · Argo CD · GitOps · Linux · IAM · observability · on-prem · air-gapped
Source and classification
Internal deployment & tooling · Evidence for this classification:
located walking distance from 4th and King Caltrain station. What you’ll do: Architect and own complex customer-hosted cloud deployments that run scalably and reliably across diverse customer environments. Triage, debug, and resolve high-severity issues end-to-end, building bulletproof automated safeguards and observability to permanently prevent regressions. Design fully automated, repeatable deployment pipelines with deep observability to proactively surface edge cases before they hit production. Drive developer velocity and build internal tooling that empower the engineering team to ship fast without sacrificing reliability or security. We would love to meet you if you have experience: Operating production Kubernetes and cloud infrastructure. Delivering on-prem or customer-hosted software Strong Linux, networking and infrastructure-as-code fundamentals Independently owning
More from the job description
We’re building the scientific intelligence platform for the physical world, to accelerate breakthroughs in semiconductors, batteries, advanced materials, aerospace, and beyond. These industries represent trillions in spend, but are still trapped in outdated software. We’re changing that by building the intelligence layer to help scientists and engineers move faster and solve core problems -- R&D through manufacturing. We have a once-in-a-generation opportunity to create a category-defining company at the intersection of AI and the physical sciences. And we’re building a world-class team to do it. We recently raised a seed round led by Greylock, with participation from Neo, BoxGroup, Liquid 2, and top angels including Jeff Dean + leadership at OpenAI and AMD. Our team (ex-Applied Intuition, Glean, SpaceX, Warp, Jane Street, Verkada) works in-person in San Francisco. Our office is located walking distance from 4th and King Caltrain station. What you’ll do: Architect and own complex customer-hosted cloud deployments that run scalably and reliably across diverse customer environments. Triage, debug, and resolve high-severity issues end-to-end, building bulletproof automated safeguards and observability to permanently prevent regressions. Design fully automated, repeatable deployment pipelines with deep observability to proactively surface edge cases before they hit production. Drive developer velocity and build internal tooling that empower the engineering team to ship fast without sacrificing reliability or security. We would love to meet you if you have experience: Operating production Kubernetes and cloud infrastructure. Delivering on-prem or customer-hosted software Strong Linux, networking and infrastructure-as-code fundamentals Independently owning incidents and communicating with customers Working with the following key technologies: Public cloud/AWS etc, Managed Kubernetes knowledge, IaC tools like Terraform GitOps/Argo CD, Linux, networking, IAM and observability tooling On-prem deployment; air-gapped experience is a bonus Bonus points if you have: Worked at an early stage startup, founded a company, or plan to start one someday. Air-gapped or restricted-network deployment experience Multi-cloud, hybrid-cloud or enterprise security experience Experience supporting data/AI infrastructure Experience or deep curiosity in science. Learn More about Altara Video Blog post TechCrunch Follow us on LinkedIn and X
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