Staff DevOps Engineer, Software, Product Operations

Lila Sciences

$192K — $272K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Expertise in DevOps, SRE, or Platform Engineering in large scale cloud environments
  • Experience in deploying to cloud (AWS, GCP) using infrastructure-as-code (Terraform, Helm)
  • Deep experience with CI/CD systems (GitHub Actions, GitLab CI, Jenkins)
  • Strong proficiency in Python or scripting languages for automation
  • Solid understanding of Kubernetes operations, including deployments and networking

Responsibilities

  • Design automated, scalable Kubernetes infrastructure for scientific services and ML pipelines
  • Implement CI/CD pipelines with best practices using GitHub Actions/GitLab CI
  • Develop infrastructure-as-code using Terraform and Helm, ensuring policy compliance
  • Manage AWS cloud infrastructure, focusing on services like EKS and logging/monitoring
  • Build platform tooling to enhance deployment, observability, and developer workflows
  • Conduct reliability engineering practices including performance optimization and incident response
  • Automate infrastructure operations and telemetry integration using Python or Go

Benefits

  • Comprehensive medical, dental, and vision coverage
  • Employer-paid life and disability insurance
  • Flexible time off with generous company-wide holidays
  • Paid parental leave
  • Educational assistance program
  • Commuter benefits including bike share memberships
  • Company-subsidized lunch program
Full Job Description
Your Impact at LILA

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.

What You'll Be Building
  • Build Kubernetes-based infrastructure 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

What You'll Need to Succeed
  • Expertise in DevOps, SRE, 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

Bonus Points For
  • Experience with GitOps tools (ArgoCD, Flux)
  • 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


Compensation

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.

Expected Base Salary Range

$192,000-$272,000 USD

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