Sr DevOps Engineer

Posted An Hour Ago
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San Francisco, CA, USA
In-Office
167K-231K Annually
Senior level
Artificial Intelligence • Software • Biotech • Generative AI
The Role
Designs and operates scalable AWS infrastructure, Kubernetes environments, CI/CD pipelines, and infrastructure-as-code systems. Builds deployment automation, observability, security scanning, access controls, and developer self-service tooling. Troubleshoots production incidents, improves reliability and cost efficiency, and establishes infrastructure standards. Collaborates with software engineers to improve deployment workflows and developer experience in a fast-paced startup environment.
Summary Generated by Built In
About Artos:

At Artos, we build tools that help biopharma companies create and manage their R&D documentation in a fraction of the time. If you’re looking to join a team whose mission is to fundamentally change the way that drug development gets done, we’d love to talk to you.


About the Role:

We're looking for a Senior DevOps Engineer to design, build, and maintain the infrastructure that powers our platform. You'll play a critical role in scaling our AWS infrastructure, improving Kubernetes environments, automating deployments, and building tools that make our engineering team more productive.

This is a hands-on role for someone who enjoys solving complex infrastructure problems, building reliable systems, and eliminating operational friction through automation. You'll help establish scalable infrastructure patterns and developer-friendly workflows that allow engineers to ship software quickly, reliably, and securely.

We value pragmatic engineering, thoughtful automation, and choosing the right tools for the problem rather than introducing complexity for its own sake.

What You'll Do:
  • Design, build, and maintain reliable, scalable AWS infrastructure across production and development environments.

  • Manage and optimize Kubernetes clusters, containerized applications, and deployment workflows.

  • Build and improve CI/CD pipelines using tools such as GitHub Actions, GitLab CI, or Argo CD, incorporating automated testing, dependency scanning, and container image scanning.

  • Develop reusable infrastructure components and automate provisioning using Terraform and infrastructure-as-code best practices.

  • Create standardized deployment patterns, infrastructure templates, and self-service tooling that improve developer productivity.

  • Implement and maintain monitoring, logging, metrics, tracing, and alerting using tools such as Prometheus, Grafana, Datadog, or similar platforms.

  • Improve infrastructure reliability, performance, availability, and cost efficiency.

  • Automate repetitive operational tasks, environment configuration, and infrastructure maintenance.

  • Integrate tools such as Trivy, Snyk, or Checkov into development and deployment workflows to identify vulnerabilities and infrastructure misconfigurations.

  • Manage cloud access controls, IAM policies, secrets management, and secure configuration practices using AWS-native services or tools such as HashiCorp Vault.

  • Troubleshoot production incidents, perform root cause analysis, and implement long-term improvements.

  • Collaborate closely with software engineers to improve deployment workflows, application performance, and overall developer experience.

  • Help establish infrastructure standards and operational practices that support a growing engineering organization.

What We're Looking For:
  • 5+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering.

  • Strong hands-on experience designing and operating production infrastructure on AWS.

  • Deep experience with Kubernetes, Docker, and container orchestration.

  • Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, Argo CD, or similar tools.

  • Strong experience with Terraform or comparable infrastructure-as-code tooling.

  • Proficiency in Python, Go, Bash, or similar scripting and programming languages.

  • Strong understanding of Linux, networking, DNS, load balancing, and distributed systems.

  • Experience with monitoring and observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry.

  • Experience with infrastructure automation, configuration management, and repeatable deployment processes.

  • Familiarity with container security scanning, dependency scanning, and infrastructure validation tools.

  • Working knowledge of AWS IAM, secrets management, and cloud networking best practices.

  • Experience troubleshooting complex production issues and improving system reliability.

  • Ability to make sound architectural decisions while balancing scalability, maintainability, cost, and operational simplicity.

  • Strong ownership mindset and the ability to work collaboratively in a fast-moving engineering environment.

Nice to Have:
  • Experience building internal developer platforms, self-service infrastructure, or standardized deployment workflows (paved roads).

  • Experience with Kubernetes packaging and configuration tools such as Helm templates or Jsonnet.

  • Familiarity with declarative configuration languages and tools such as ytt/Starlark, CUE, or Dhall.

  • Experience evaluating configuration and templating approaches based on expressiveness, maintainability, and operational practicality.

  • Experience with GitOps workflows using Argo CD or Flux.

  • Experience with Kubernetes operators, service meshes, or advanced cluster networking.

  • Experience with cloud security and infrastructure scanning tools such as Trivy, Snyk, Checkov, or tfsec.

  • Familiarity with policy-as-code tools such as Open Policy Agent (OPA), Kyverno, or HashiCorp Sentinel.

  • Experience with secrets management tools such as HashiCorp Vault or AWS Secrets Manager.

  • Experience supporting multi-tenant SaaS applications or distributed systems at scale.

  • Experience with AI/ML infrastructure, data pipelines, or compute-intensive workloads.

  • Experience operating infrastructure in regulated environments or supporting SOC 2 compliance requirements.

  • Experience working in an early-stage or rapidly scaling startup.

What Success Looks Like:
  • Cloud infrastructure is reliable, scalable, observable, and cost-efficient.

  • Kubernetes environments and deployment pipelines are stable, automated, and easy to maintain.

  • Engineers can provision infrastructure and deploy applications with minimal operational friction.

  • Infrastructure changes are repeatable, version-controlled, and consistently validated.

  • Monitoring and alerting provide clear visibility into system health and performance.

  • Security checks are integrated into existing engineering workflows without creating unnecessary bottlenecks.

  • Manual operational work is reduced through automation and improved developer tooling.

  • The engineering organization has infrastructure foundations that support continued growth and faster software delivery.


Other Information:

Very comfortable working in a fast-paced and intense startup environment

Willing to work in-person in our office in Mission Bay 4-5 days/week

Likes matcha KitKats, believes every LLM prompt is just Schrödinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system

Skills Required

  • 5+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering
  • Hands-on experience designing and operating production infrastructure on AWS
  • Deep experience with Kubernetes, Docker, and container orchestration
  • Experience building and maintaining CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, Argo CD, or similar tools
  • Strong experience with Terraform or comparable infrastructure-as-code tooling
  • Proficiency in Python, Go, Bash, or similar scripting and programming languages
  • Strong understanding of Linux, networking, DNS, load balancing, and distributed systems
  • Experience with monitoring and observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry
  • Experience with infrastructure automation, configuration management, and repeatable deployment processes
  • Familiarity with container security scanning, dependency scanning, and infrastructure validation tools
  • Working knowledge of AWS IAM, secrets management, and cloud networking best practices
  • Experience troubleshooting complex production issues and improving system reliability
  • Ability to make architectural decisions balancing scalability, maintainability, cost, and operational simplicity
  • Strong ownership mindset and collaborative communication skills
  • Experience building internal developer platforms, self-service infrastructure, or standardized deployment workflows
  • Experience with Kubernetes packaging and configuration tools such as Helm templates or Jsonnet
  • Familiarity with ytt/Starlark, CUE, or Dhall
  • Experience evaluating configuration and templating approaches
  • Experience with GitOps workflows using Argo CD or Flux
  • Experience with Kubernetes operators, service meshes, or advanced cluster networking
  • Experience with Trivy, Snyk, Checkov, or tfsec
  • Familiarity with OPA, Kyverno, or HashiCorp Sentinel
  • Experience with HashiCorp Vault or AWS Secrets Manager
  • Experience supporting multi-tenant SaaS applications or distributed systems at scale
  • Experience with AI/ML infrastructure, data pipelines, or compute-intensive workloads
  • Experience operating infrastructure in regulated environments or supporting SOC 2 compliance
  • Experience working in an early-stage or rapidly scaling startup
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The Company
21 Employees
Year Founded: 2023

What We Do

Artos AI develops a generative-AI platform for biopharma and life-sciences organizations. Its software helps clinical development, medical writing, CMC, and regulatory teams create, manage, trace, and collaborate on documents used in regulatory submissions, including INDs, NDAs, and BLAs. By turning structured and unstructured data into submission-ready materials, Artos aims to shorten development timelines and bring treatments to patients faster and more efficiently.

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