Senior DevOps Engineer

About the role

Aviatrix® is pioneering the Cloud Native Security Fabric - the architecture the Containment Era requires. The Cloud Native Security Fabric governs every workload communication path across every cloud, every VPC, every Kubernetes cluster, and every serverless function, from a single policy plane. One rule. Universal propagation. Enforced at the workload, not at a chokepoint. Trusted by more than 500 of the world's leading enterprises. For more information, visit aviatrix.ai . We are looking for a seasoned Senior DevOps Engineer to join our team and take ownership of our CI/CD ecosystem, cloud infrastructure automation, and developer platform. This is a journey-level, fully qualified position where you will independently design and drive solutions across complex, diverse projects - bringing both technical depth and collaborative leadership to everything you do. You will work at the intersection of infrastructure engineering, AI-driven tooling, and modern cloud operations, partnering closely with development and TechOps teams to accelerate delivery cycles and ensure the reliability, security, and scalability of our systems.

Responsibilities

• Design, implement, and maintain robust, scalable CI/CD pipelines across multiple environments, applying industry best practices to optimize delivery speed and system reliability.
• Automate the provisioning and lifecycle management of cloud resources (VMs, EC2, and more) using Infrastructure as Code - with Terraform as the primary tool - ensuring consistent, repeatable, and auditable deployments.
• Manage and optimize cloud networking configurations, supporting complex developer workflows and infrastructure scalability requirements.
• Integrate AI and large language model (LLM) capabilities into DevOps tooling and developer workflows, including leveraging Model Context Protocol (MCP) for intelligent automation and context-aware pipeline tooling.
• Collaborate with engineering and operations teams to identify bottlenecks, reduce toil, and continuously improve the release process.
• Apply security best practices to deployment pipelines and cloud infrastructure, proactively identifying and remediating vulnerabilities.
• Monitor, observe, and optimize infrastructure performance, taking initiative to resolve complex issues before they impact customers.
• Evaluate emerging tools and technologies - particularly in the AI/LLM space - and provide guidance on how to incorporate them effectively into organization workflows.
• Communicate technical strategies and recommendations clearly to senior internal and external stakeholders, adapting your approach to diverse audiences and often driving alignment on difficult decisions.

Requirements

• 5+ years of related DevOps/infrastructure engineering experience (or 3 years with a Master's degree or equivalent experience).
• Deep, hands-on expertise with Terraform for infrastructure as code - this is a must-have.
• Hands-on, production-level experience building and deploying AI/LLM-integrated systems - this is a must-have. You have worked directly with large language model APIs, designed AI-assisted workflows, and shipped real tooling powered by LLMs in an engineering or DevOps context.
• Hands-on, production-level experience with Model Context Protocol (MCP) - this is a must-have. You have implemented MCP-based integrations to build intelligent, context-aware developer tools, automation pipelines, or agent workflows, not just read about it.
• Strong command of CI/CD platforms (e.g., GitHub Actions, GitLab CI, Jenkins, CircleCI, or similar).
• Experience provisioning and managing cloud infrastructure on AWS, GCP, or Azure (EC2, VMs, VPCs, IAM, etc.).
• Solid understanding of cloud networking concepts (VPCs, subnets, security groups, load balancers, DNS).
• Demonstrated ability to work independently, resolve ambiguous and complex problems, and deliver high-quality solutions with minimal supervision.
• Preferred:
• Experience with Kubernetes, Helm, or container orchestration platforms.
• Familiarity with GitOps workflows (e.g., ArgoCD, Flux).
• Scripting proficiency in Python, Bash, or Go.
• Knowledge of observability tooling (Datadog, Prometheus/Grafana, OpenTelemetry).
• Experience building internal developer platforms (IDPs).
• US Pay Range :

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