Kaseya^® is the leading provider of complete IT infrastructure and security management solutions for Managed Service Providers (MSPs) and internal IT organizations worldwide powered by AI. Kaseya’s best-in-breed technologies allow organizations to efficiently manage and secure IT to drive sustained business success. Kaseya has achieved sustained, strong double-digit growth over the past several years and is backed by Insight Venture Partners www.insightpartners.com), a leading global private equity firm investing in high-growth technology and software companies that drive transformative change in the industries they serve.

Founded in 2000, Kaseya currently serves customers in over 20 countries across a wide variety of industries and manages over 15 million endpoints worldwide. To learn more about our company and our award-winning solutions, go to www.Kaseya.com and for more information on Kaseya’s culture.

Kaseya is not your typical company. We are not afraid to tell you exactly who we are and our expectations. The thousands of people that succeed at Kaseya are prepared to go above and beyond for the betterment of our customers.

WHAT YOU’LL DO:

Join the dynamic team at Kaseya as a Staff AI DevOps Engineer. Build the automated backbone of our AI platform, driving CI/CD, Infrastructure as Code (IaC), and observability to enable secure, scalable, and rapid deployment of intelligent agents. You’ll lead the implementation of cutting-edge DevOps, DevSecOps, and MLOps practices that support continuous delivery, resilient infrastructure, and high-performance AI workloads. Your work will ensure our platform is production-ready, cost-efficient, and built for speed, security, and scale.

WHAT WE ARE LOOKING FOR:

We’re looking for a DevOps engineer who thrives in cross-functional environments and brings a strong sense of ownership to infrastructure reliability and automation. You’re a clear communicator who can collaborate across AI, platform, and security teams, document complex systems, and present infrastructure strategies and metrics to technical leadership. You lead by example, mentor others in best practices, and drive continuous improvement across the stack.

THE SCHEDULE:
This position is 100% remote.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Design and maintain CI/CD pipelines to support rapid, reliable delivery of AI platform components and intelligent agents
Implement Infrastructure as Code (IaC) and GitOps practices to manage scalable, secure, and reproducible environments
Build and manage Kubernetes-based infrastructure, including custom operators and GPU workload orchestration
Integrate MLOps tools and workflows to streamline the AI model lifecycle from training to deployment
Deploy and maintain observability stacks for real-time monitoring, tracing, and alerting across distributed systems
Enforce DevSecOps practices, including automated security scanning, policy-as-code, and compliance automation
Optimize cloud infrastructure for performance, cost-efficiency, and resilience

WHAT YOU’LL BRING:

5-7+ years of experience in DevOps, SRE, or platform engineering
Expert with CI/CD pipeline design and tools (e.g., Jenkins, GitLab CI, ArgoCD, GitHub Actions)
Deep Infrastructure as Code (IaC) experience (e.g., Terraform, CloudFormation)
Expert-level Kubernetes administration and workload management, including custom controllers/operators
Experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, Seldon Core, Vertex AI Pipelines, SageMaker MLOps)
Proficiency in implementing observability stacks (e.g., Prometheus, Grafana, Jaeger, OpenTelemetry, ELK)
Advanced scripting skills (Python, Bash, Go)
Strong understanding of cloud security best practices and automation (e.g., SAST, DAST)
Experience with GitOps workflows and cost optimization strategies for cloud-based AI/ML workloads
Bachelor's degree in Computer Science, DevOps Engineering, or a related field
Preferred: Certified Kubernetes Administrator (CKA), DevOps Engineer certifications (AWS, Azure, GCP), or FinOps certification
Additional certifications in MLOps platforms or cloud security are a plus

Nice to Have:

Experience with GPU cluster management and scheduling (e.g., Slurm, NVIDIA AI Enterprise, MIG)
Infrastructure for federated learning or edge AI
Proficiency in policy-as-code frameworks (e.g., Open Policy Agent, Kyverno)
AI model serving optimization and inference acceleration (e.g., TensorRT, ONNX Runtime)
Experience building and managing serverless infrastructure for AI
FinOps certification or strong practical experience

Join the Kaseya growth rocket ship and see how we are #ChangingLives !

Additional information
Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.

Staff AI DevOps Engineer

Job Description