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About
Location: San Francisco Bay Area Type: Full-Time Compensation: Competitive salary + meaningful equity (founding tier) Backed by 8VC, we're building a world-class team to tackle one of the industry's most critical infrastructure problems. About the Role
We're building an AI-native, multi-tenant enterprise platform for complex domains in industrial verticals. In this architecture, DevOps isn't just about shipping features it's about operationalizing intelligent agents, ensuring traceability across AI systems, and supporting mission-critical ML infrastructure at scale. We're looking for a DevOps engineer who can own infrastructure from Day 1 automating everything from CI/CD and observability to cloud governance and security. You'll work with a highly technical team building real-time AI pipelines and multi-agent systems. If you want to be the person who makes the platform run fast, secure, reliable, and explainable this is your role. Responsibilities
Build and maintain scalable cloud infrastructure across AWS/GCP/Azure with a focus on secure, tenant-isolated deployments Own and evolve CI/CD systems (e.g. GitHub Actions, ArgoCD) with progressive rollout, testing, and rollback flows Establish observability tooling across services, agents, and pipelines (OpenTelemetry, Prometheus, Grafana, Sentry) Implement policy-as-code (OPA, Rego) for deployment safety, RBAC, audit logging, and approval workflows Define and enforce SLAs, uptime targets (99.99%+), incident response, and remediation workflows Secure infrastructure: IAM, VPC, encryption, key management, image scanning, secrets rotation Automate deployments, infrastructure provisioning (Terraform, Helm), and environment replication What We're Looking For
Core Experience: 410+ years in DevOps, platform engineering, or SRE in production-grade systems Strong experience with Docker, Kubernetes (EKS/GKE), Terraform or Pulumi Hands-on experience deploying and monitoring distributed cloud-native systems Familiar with GitOps practices, CI/CD design, progressive delivery, and secure SDLC Clear understanding of how to implement monitoring, alerting, and failure simulation in dynamic environments Engineering Mindset: Obsessed with reliability, latency, uptime, and repeatability Security-aware and compliance-conscious Proactive you don't wait for alerts to fix things Comfortable collaborating with backend, AI, and data teams Bonus: Agent-Native / ML Ops Capabilities: Experience running LLM orchestration frameworks (e.g. LangChain, LangGraph, Dust, ReAct agents) Building retrieval-augmented generation (RAG) pipelines and deploying them safely and repeatably Familiarity with vector DBs (Weaviate, Qdrant, Pinecone) and embedding pipelines Monitoring and governing long-running or multi-agent chains Auditability and replay systems for agent decision-making Serving fine-tuned or open-source LLMs with model versioning and GPU scaling (e.g. vLLM, TGI) Interest in auto-remediation using agents (e.g. observability + alert ? insight ? response via LLM) Why This Role Matters
DevOps is the nervous system of the platform every agent, every data fabric component, every pipeline flows through what you build. This is a rare opportunity to design that system early, the right way, and future-proof it for scale, compliance, and trust. If you're excited by intelligent systems, distributed data, and deeply technical infrastructure problems and you want your work to have immediate real-world impact we'd love to hear from you.
Languages
- English
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