Liminal

Cloud DevOps Engineer

Liminal

full-time

Posted on:

Location Type: Hybrid

Location: Salt Lake City • Utah • United States

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Salary

💰 $180,000 - $210,000 per year

Job Level

SeniorLead

Tech Stack

BigQueryCloudDistributed SystemsDockerGoogle Cloud PlatformKubernetesPythonTerraform

About the role

  • Own the full lifecycle of infrastructure, deployment systems, and AI operations
  • Design, build, and maintain CI/CD pipelines (GitHub Actions, GitLab CI/CD)
  • Deploy and manage cloud infrastructure on GCP using Terraform
  • Build and maintain data pipelines supporting ML and AI workflows
  • Design and operate AI-powered workflows, including LLM integrations and agents
  • Support tool orchestration, prompt/context management, and AI-enabled systems
  • Build internal automation to improve engineering productivity using AI
  • Implement containerized systems using Docker and Kubernetes
  • Monitor and optimize systems using tools like Datadog
  • Troubleshoot production issues across: Cloud infrastructure, CI/CD pipelines, Data pipelines, AI systems (latency, failures, reliability)
  • Partner with engineering, data, and product teams to productionize AI capabilities
  • Drive adoption of DevOps, AI Ops, and automation best practices

Requirements

  • 8+ years of experience in DevOps, cloud infrastructure, or platform engineering, or AI Ops within SaaS or cloud-based environments
  • Strong hands-on experience with: GCP (Cloud Run, BigQuery, etc.)
  • Terraform or similar IaC tools
  • CI/CD systems (GitHub Actions, GitLab CI/CD)
  • Docker and Kubernetes
  • Data pipelines and distributed systems
  • Experience working with AI systems, including: Deploying or supporting ML/LLM systems in production
  • AI-assisted engineering tools (Claude Code, Cursor, Codex, etc.)
  • Understanding of agent workflows or AI tooling ecosystems
  • Experience with monitoring, logging, and alerting systems (e.g., Datadog)
  • Strong scripting skills (Python, Bash, or similar)
  • Understanding of IAM, security, and cloud best practices
  • Ability to troubleshoot complex production issues across systems
  • Clear communication and collaboration skills
  • A bias toward ownership — you solve problems end-to-end
  • Bonus Points: Experience with agent frameworks (LangChain, LangGraph, CrewAI, etc.)
  • Experience building AI-powered automation or internal tooling
  • Experience with serverless and cloud-native architectures
  • Experience with ML/LLM lifecycle management (evaluation, monitoring, versioning)
  • Experience scaling infrastructure in a high-growth environment
Benefits
  • Equity
  • Performance bonus tied to company-wide revenue share
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
GCPTerraformCI/CDDockerKubernetesPythonBashAI systemsData pipelinesML/LLM lifecycle management
Soft Skills
clear communicationcollaborationproblem-solvingownership