Fabrion
Join to apply for the
DevOps Engineer (Founding Team)
role at
Fabrion
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, and 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%+) and incident response and remediation workflows
Secure infrastructure: IAM, VPC, encryption, key management, image scanning, and 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
Familiarity 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.
#J-18808-Ljbffr
DevOps Engineer (Founding Team)
role at
Fabrion
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, and 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%+) and incident response and remediation workflows
Secure infrastructure: IAM, VPC, encryption, key management, image scanning, and 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
Familiarity 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.
#J-18808-Ljbffr