Software Engineer (TechOps)

Requirements

• Strong experience with Docker, Terraform and at least one major Cloud Platform
• Strong Python programming
• Strong hands‑on experience managing Kubernetes clusters
• Extensive experience with modern DevOps (CI/CD, release management, automation)
• Clear understanding of Infrastructure as Code
• Experience with Helm/Kustomize/Kapitan or similar deployment tools
• Experience with Grafana/Prometheus/Splunk or similar monitoring/observability technologies
• Ability to independently deliver solutions and work effectively in cross‑functional teams
• (Desirable) Experience with Google Cloud Platform (GCP)
• (Desirable) Strong foundations in software engineering before moving into a technical operations role
• (Desirable) Proficiency in identifying and mitigating security risks
• (Desirable) Experience with GitHub Actions
• (Desirable) Experience supporting machine learning cloud infrastructure

What the job involves

• You will be working on our groundbreaking platform that will transform the biopharmaceutical world as we know it
• You’ll join our Platform group, where you partner with leading engineers, scientists and ML researchers to build the critical foundations driving that transformation
• You’ll be working as part of a small and highly efficient team on all parts of cloud infrastructure and software lifecycle
• We believe Isomorphic is best of both worlds: a dynamic startup where things happen fast with a secure Alphabet backing and a long‑term vision
• We’re still at a relatively early stage in our journey, with a level of ambiguity as we continuously learn from each other, so you will need to build on your previous experience and show initiative in order to fully carve out your contribution in this newly created role
• Design, operate, manage and refine research, development, and production cloud infrastructure (GCP, K8s, Docker, Terraform, Kapitan, etc.)
• Develop and manage tools and processes to enhance software development practices
• Contribute to core technical decisions (e.g. choice of tooling, infrastructure, and architectural design)
• Partner and collaborate with a diverse set of teams including science (drug discovery), research (machine learning), product, business development and operations

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