DevOps Engineer (Founding Team)

Fabrion; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity

Job summary

A technology startup in the San Francisco Bay Area is seeking a DevOps Engineer to build and maintain scalable cloud infrastructure. The ideal candidate will have 4–10+ years of experience and strong skills in Docker, Kubernetes, and CI/CD systems. This role offers competitive compensation and meaningful equity as part of the founding team. If you're motivated by solving complex infrastructure challenges in AI, we want to hear from you.

Qualifications

• 4–10+ years in DevOps or related fields.
• Strong experience with Docker and Kubernetes.
• Hands-on experience with distributed cloud-native systems.

Responsibilities

• Build and maintain scalable cloud infrastructure.
• Own and evolve CI/CD systems.
• Establish observability tooling across services.
• Implement policy-as-code for deployment safety.
• Define SLAs and incident response workflows.
• Secure infrastructure and automate deployments.

Skills

Docker

Kubernetes

Terraform

CI/CD

Cloud-native systems

Monitoring and alerting

Tools

GitHub Actions

ArgoCD

OpenTelemetry

Prometheus

Grafana

Sentry

Job description

Overview

DevOps Engineer (Founding Team)

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:

• 4–10+ 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

• We’re building an agentic, AI-native platform from the ground up. Experience here isn’t required, but would be a strong differentiator:
• 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.