Builds and maintains scalable infrastructure, CI/CD pipelines, and observability for AI-powered developer tools. Requires 5+ years DevOps/SRE experience, Kubernetes/Docker expertise, and cloud/IaC proficiency.
Education: Degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
Experience: 5+ years of experience in a DevOps, Infrastructure, or SRE role at a fast-paced tech company or startup
Tooling: Expert-level proficiency with CI/CD systems (GitHub Actions, ArgoCD, etc.), Docker, and Kubernetes
Infrastructure: Expert with cloud providers (AWS/GCP), distributed systems architecture and implementation, IaC tools (Terraform, Pulumi), and secrets management (Vault, SSM, etc.)
Observability: Strong understanding of logging, metrics, and monitoring in large-scale distributed systems (e.g., Grafana, Prometheus, ELK, Datadog)
Collaboration: Effective at partnering with backend and ML teams to deliver stable, high-velocity systems
Security: Experience building with best practices in cloud and application-level security
Leads end-to-end integration of agentic platform tools with clients, backends, and cloud ops on Kubernetes. Requires 7+ years experience, strong Python, HTTP/auth expertise, and cross-functional collaboration for reliable tool contracts and releases.
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Leads development of DataHub's ingestion framework, building scalable metadata systems, APIs, and event-driven architectures for enterprise AI and data platforms. Requires 4+ years in distributed systems and advanced Python expertise.
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Designs, builds, and maintains enterprise-grade Kubernetes operator in Rust for SMBP, focusing on API architecture, networking, security, observability, multi-cloud deployment, and operational tooling. Collaborates with customers to meet production Kubernetes needs.