DevOps Engineer - Startup

The Organization

We are pioneering a context-aware architecture designed for enterprise AI that maps organizational decision-making by analyzing operational data. Our system utilizes a dynamic Context Graph to represent business intelligence, allowing next-generation AI agents to navigate and utilize complex insights.

The Role

We are looking for an exceptional DevOps Engineer to take full ownership of our multi-cloud infrastructure. In this position, you will develop and optimize the production systems that support our AI-driven platform across AWS, GCP, and Azure. This role is a perfect fit for engineers who want to build the backbone of a cutting-edge AI product by combining cloud infrastructure, Kubernetes orchestration, and CI/CD automation.

Key Responsibilities

• Infrastructure as Code: Design and manage multi-cloud environments using Terraform and Terragrunt, including EKS clusters, networking, and high-scale databases.
• Deployment & Automation: Build and maintain CI/CD pipelines for a microservices architecture involving 14+ Kubernetes workloads deployed via Helm.
• Observability: Utilize Datadog (APM, logs, metrics, NPM) to ensure system reliability and meet production SLAs for enterprise customers.
• Security: Implement a security-first infrastructure, including WAF policies, IAM/Pod Identity, network segmentation, and secrets management using External Secrets Operator and AWS Secrets Manager.
• Access Management: Develop authorization mechanisms for various interfaces, including APIs, SDKs, and MCP.
  
  

• Experience: At least 5 years in DevOps, SRE, or Infrastructure roles, with prior experience in a startup environment.
• Kubernetes: Strong experience with EKS/GKE cluster management, Helm charts, Gateway API, and scaling strategies.
• IaC: Solid proficiency in Terraform and Terragrunt, specifically with module design, state management, and multi-environment configurations.
• AWS Proficiency: Deep knowledge of VPC, ALB, RDS, ElastiCache, S3, ECR, IAM, Secrets Manager, WAF, and Bedrock.
• GCP Knowledge: Experience with GKE, VPC, Cloud Armor, Cloud DNS, and Cloud Load Balancing is a significant advantage.
• Monitoring: Proficiency with Datadog or equivalent tools like Prometheus and Grafana.
• Networking: Solid understanding of VPC design, security groups, DNS, and TLS/cert management.
• Operations: Experience with production systems, including incident response, capacity planning, and disaster recovery.
• Mindset: An autonomous player with a "get shit done" attitude, professional curiosity, and a proactive approach to solving complex challenges.
  
  

• Experience supporting AI/ML workloads, including LLM inference and GPU scheduling.
• Knowledge of MongoDB operations, including Kubernetes Operator and backup/restore.
• Experience with WebSocket infrastructure such as Soketi or Pusher.
• Multi-cloud cost optimization or hybrid deployment experience.