{"id":3901425,"url":"https://alion.io/job/artos-sr-devops-engineer","title":"Sr DevOps Engineer","company":{"id":7635,"name":"Artos","domain":"artosai.com","url":"https://alion.io/company/artos","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":166500,"max":231000,"currency":"USD","period":"year","gross":null,"usd_annual":231000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Bash","optional":false},{"name":"Checkov","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Datadog","optional":false},{"name":"DNS","optional":false},{"name":"Docker","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"HashiCorp Vault","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Snyk","optional":false},{"name":"Terraform","optional":false},{"name":"Trivy","optional":false},{"name":"GitOps","optional":true},{"name":"Helm","optional":true},{"name":"Jsonnet","optional":true},{"name":"Kyverno","optional":true},{"name":"LLM","optional":true},{"name":"Open Policy Agent","optional":true},{"name":"SOC 2","optional":true},{"name":"tfsec","optional":true}],"status":"live","first_seen_at":"2026-11-06T20:54:32Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-07T00:56:31Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About Artos:\nAt 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.\nAbout the Role:\nWe'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.\nThis 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.\nWe value pragmatic engineering, thoughtful automation, and choosing the right tools for the problem rather than introducing complexity for its own sake.\nWhat You'll Do:\nDesign, build, and maintain reliable, scalable AWS infrastructure across production and development environments.\n\nManage and optimize Kubernetes clusters, containerized applications, and deployment workflows.\n\nBuild 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.\n\nDevelop reusable infrastructure components and automate provisioning using Terraform and infrastructure-as-code best practices.\n\nCreate standardized deployment patterns, infrastructure templates, and self-service tooling that improve developer productivity.\n\nImplement and maintain monitoring, logging, metrics, tracing, and alerting using tools such as Prometheus, Grafana, Datadog, or similar platforms.\n\nImprove infrastructure reliability, performance, availability, and cost efficiency.\n\nAutomate repetitive operational tasks, environment configuration, and infrastructure maintenance.\n\nIntegrate tools such as Trivy, Snyk, or Checkov into development and deployment workflows to identify vulnerabilities and infrastructure misconfigurations.\n\nManage cloud access controls, IAM policies, secrets management, and secure configuration practices using AWS-native services or tools such as HashiCorp Vault.\n\nTroubleshoot production incidents, perform root cause analysis, and implement long-term improvements.\n\nCollaborate closely with software engineers to improve deployment workflows, application performance, and overall developer experience.\n\nHelp establish infrastructure standards and operational practices that support a growing engineering organization.\n\nWhat We're Looking For:\n5+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering.\n\nStrong hands-on experience designing and operating production infrastructure on AWS.\n\nDeep experience with Kubernetes, Docker, and container orchestration.\n\nExperience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, Argo CD, or similar tools.\n\nStrong experience with Terraform or comparable infrastructure-as-code tooling.\n\nProficiency in Python, Go, Bash, or similar scripting and programming languages.\n\nStrong understanding of Linux, networking, DNS, load balancing, and distributed systems.\n\nExperience with monitoring and observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry.\n\nExperience with infrastructure automation, configuration management, and repeatable deployment processes.\n\nFamiliarity with container security scanning, dependency scanning, and infrastructure validation tools.\n\nWorking knowledge of AWS IAM, secrets management, and cloud networking best practices.\n\nExperience troubleshooting complex production issues and improving system reliability.\n\nAbility to make sound architectural decisions while balancing scalability, maintainability, cost, and operational simplicity.\n\nStrong ownership mindset and the ability to work collaboratively in a fast-moving engineering environment.\n\nNice to Have:\nExperience building internal developer platforms, self-service infrastructure, or standardized deployment workflows (paved roads).\n\nExperience with Kubernetes packaging and configuration tools such as Helm templates or Jsonnet.\n\nFamiliarity with declarative configuration languages and tools such as ytt/Starlark, CUE, or Dhall.\n\nExperience evaluating configuration and templating approaches based on expressiveness, maintainability, and operational practicality.\n\nExperience with GitOps workflows using Argo CD or Flux.\n\nExperience with Kubernetes operators, service meshes, or advanced cluster networking.\n\nExperience with cloud security and infrastructure scanning tools such as Trivy, Snyk, Checkov, or tfsec.\n\nFamiliarity with policy-as-code tools such as Open Policy Agent (OPA), Kyverno, or HashiCorp Sentinel.\n\nExperience with secrets management tools such as HashiCorp Vault or AWS Secrets Manager.\n\nExperience supporting multi-tenant SaaS applications or distributed systems at scale.\n\nExperience with AI/ML infrastructure, data pipelines, or compute-intensive workloads.\n\nExperience operating infrastructure in regulated environments or supporting SOC 2 compliance requirements.\n\nExperience working in an early-stage or rapidly scaling startup.\n\nWhat Success Looks Like:\nCloud infrastructure is reliable, scalable, observable, and cost-efficient.\n\nKubernetes environments and deployment pipelines are stable, automated, and easy to maintain.\n\nEngineers can provision infrastructure and deploy applications with minimal operational friction.\n\nInfrastructure changes are repeatable, version-controlled, and consistently validated.\n\nMonitoring and alerting provide clear visibility into system health and performance.\n\nSecurity checks are integrated into existing engineering workflows without creating unnecessary bottlenecks.\n\nManual operational work is reduced through automation and improved developer tooling.\n\nThe engineering organization has infrastructure foundations that support continued growth and faster software delivery.\n\nOther Information:\nVery comfortable working in a fast-paced and intense startup environment\nWilling to work in-person in our office in Mission Bay 4-5 days/week\nLikes 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 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