Home › Companies › fal › Software Engineer, Site Reliability
Software Engineer, Site Reliability
Fal · San Francisco · Remote · Active · $180,000 / year · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Fal |
| Title | Software Engineer, Site Reliability |
| Normalized title | - |
| Department / team | Engineering |
| Location | San Francisco, CA, United States |
| Work model | Remote / Remote |
| Employment type | - |
| Salary | $180,000 / year |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2026-02-23 / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-19 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Fal. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Engineering. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Fal |
| Source | 00cad292-f66b-476d-a9f7-2cd97898a6d0 |
| ATS provider | Greenhouse |
Description
fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.
As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.
About this role
You are a seasoned SRE who keeps production infrastructure running at scale. You own the reliability and availability of customer-facing systems — from Kubernetes clusters to deployment pipelines to the networking layer that connects it all. You think in SLOs, automate ruthlessly, and treat every incident as a chance to make the system better.
Key Responsibilities
Own and operate our Kubernetes infrastructure: cluster lifecycle, upgrades, networking, and multi-tenant isolation for customer workloads
Build and maintain CI/CD pipelines and deployment infrastructure
Leverage AI to an extreme level to automate analysis and resolution of production issues, and improve software development speed, reliability and maintainability
Build dashboards, alerting, and anomaly detection across our systems
Define and enforce SLOs and build out incident response processes
Manage and improve our networking, load balancing, and service mesh configurations
Drive reliability improvements across the stack through automation, runbooks, and chaos engineering
Requirements
5+ years experience in managing critical production systems and software development workflows
Strong production experience setting up and operating Kubernetes at scale, using infrastructure-as-code (Terraform, Ansible)
Deep knowledge of Linux networking, container networking (CNI plugins, VXLAN, BGP), and DNS
Experience building CI/CD systems and GitOps workflows (FluxCD, ArgoCD)
Proficiency in Python and either Go or Bash for tooling and automation
Strong experience with logging, monitoring and alerting (Prometheus, Grafana, Loki, Thanos, VictoriaMetrics, Datadog)
Excellent communication and ability to drive technical decisions across teams
Self-starter who executes quickly, takes ownership, and constantly seeks improvement
Nice to have
Experience with managing GPU and AI/ML workloads
Experience with kernel-based monitoring and routing (eBPF, XDP)
Experience with security tooling (Falco, Coroot, SIEM)
Experience with bare metal Kubernetes networking (Calico, Cilium, MetalLB)
Experience with distributed storage systems (Ceph, Longhorn, etc.)
Compensation
$180,000-250,000 plus equity + benefits (Range is based across 3 levels MId, Senior and Staff)
Location
San Francisco, CA (willing to consider remote for Senior and Staff levels)
What we offer at fal
Interesting and challenging work
A lot of learning and growth opportunities
We are currently hiring in downtown San Francisco.
We offer relocation assistance to San Francisco.
Health, dental, and vision insurance (US)
Regular team events and offsites
Full job record
| Job ID | 48692d07c861b965638241674509a21de00cbde1 |
| Org ID | 144222fa-e13c-4bb3-be7f-89ec0ca39bac |
| Source ID | 00cad292-f66b-476d-a9f7-2cd97898a6d0 |
| Board ID | 00cad292-f66b-476d-a9f7-2cd97898a6d0 |
| Provider | greenhouse |
| Provider Job Key | 4146019009 |
| Title | Software Engineer, Site Reliability |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Engineering |
| Team | — |
| Employment Type | — |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | Compensation $180,000-250,000 plus equity + benefits (Range is based across 3 levels MId, Senior and |
| Salary Min | 180,000 |
| Salary Max | — |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://job-boards.greenhouse.io/fal/jobs/4146019009 |
| Apply URL | https://job-boards.greenhouse.io/fal/jobs/4146019009 |
| First Seen At | 2026-05-29 22:55:27Z |
| Last Seen At | 2026-06-19 07:31:43Z |
| Last Checked At | 2026-06-19 07:31:43Z |
| Last Changed At | 2026-05-29 22:55:27Z |
| Inactive At | — |
| Source Posted At | 2026-02-23 18:43:02Z |
| Source Updated At | 2026-05-21 19:54:05Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=fal/date=2026-06-19/2026-06-19T07-31-42-972Z-a39f4f0983fcc0cded6a645ddfac2d220d8bdaecbe7a398575c740afef5dbde2.json |
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