USAStaff DevOps Engineer, Software, Product Operations
2 мес. назад
USALead
kubernetesterraformhelmawsgithub actionsgitlab ciopakyverno
The Staff/Principal DevOps Engineer will design, implement, and optimize infrastructure and delivery platforms for scientific services and ML pipelines in cloud and Kubernetes environments.
Будет плюсом
- SRE practices: observability platforms, chaos engineering, incident management
- Securing ML/AI pipelines (model registries, training clusters, inference gateways)
- Experience in regulated/audit-heavy environments (SOC 2, ISO 27001)
- Supply chain security maturity: SBOMs, image signing, SLSA concepts
- Administering static analysis platforms (custom quality profiles, security hotspot triage) and scaling browser-based test suites across parallel CI environments
- Prior startup/high-growth experience balancing velocity with reliability
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Условия
- We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
- U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
- International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Другое
- The Staff/Principal DevOps Engineer will drive the design, implementation, and optimization of our infrastructure and delivery platforms. This role bridges platform engineering, site reliability, and DevOps practices, building scalable, automated systems that enable fast, reliable software delivery across cloud and Kubernetes environments. You will collaborate with software engineers, lab scientists, and ML engineers to build infrastructure that powers automated scientific analysis, experiment orchestration, and more.
- Build Kubernetes-based systems supporting scientific services, ML pipelines, and platform workloads; including production hardening, RBAC, network policies, and Pod Security Standards
- CI/CD pipelines with GitHub Actions/GitLab CI implementing best practices: build attestations, SBOM generation, dependency scanning, and container image hardening
- Infrastructure-as-code with Terraform and Helm; policy-as-code guardrails (OPA/Kyverno/Checkov) with drift detection
- AWS cloud infrastructure: EKS clusters, IAM least privilege, VPC/PrivateLink networking, KMS/Secrets Manager, ECR, S3, and centralized logging/monitoring
- Platform tooling to streamline deployment, observability, and developer workflows, enabling self-service with secure defaults
- Reliability engineering: SLOs/SLIs, incident response, capacity planning, and performance optimization throughout the stack
- Software supply chain practices: artifact signing, registry governance and vulnerability management
- QA and testing infrastructure: static analysis and code quality gate enforcement in CI pipelines, automated end-to-end and browser-based regression test suites, ephemeral test environments for PR-based validation, and pre-merge quality checks
- Automation and tooling in Python or Go to improve infrastructure operations and integrate telemetry with observability platforms
- Expertise in DevOps, SRE, Systems Engineering, or Platform Engineering in large scale cloud environments
- Expertise in deploying to cloud environments (AWS, GCP, etc) using infrastructure-as-code (Terraform, Helm) and containerization
- Deep experience with CI/CD systems (GitHub Actions, GitLab CI, or Jenkins) and GitOps practices
- Strong proficiency in Python/scripting languages for automation and tooling
- Strong understanding of Kubernetes operations: deployments, networking, storage, observability, and troubleshooting
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at
- Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
- Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .
- Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.