Baseten

AI

SRE

$135–285k San Francisco, California, United States; New York, New York, United States; United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“SRE at Baseten. Skills: Kubernetes, Observability, Infrastructure-as-code, Incident management, Reliability engineering. Own the reliability of Baseten's multi-cloud Kubernetes infrastructure. Incident response”

What You'll Achieve.

Keep our platform reliable at scale; Empower the broader organization to operate confidently

Industry & Context.

AI
Problems you'll solve

Navigate ambiguity; Make principled tradeoffs; Avoid unnecessary complexity

What They're Looking For.

Must Have

Extensive hands-on experience with Kubernetes, Experience in building and maintaining scalable infrastructure, Foundation in observability tooling: metrics (VictoriaMetrics, Prometheus), logging (Loki, ELK), dashboards (Grafana), and alerting pipelines, Experience with infrastructure-as-code (Terraform, Helm), Experience with GitOps workflows (Flux CD, ArgoCD), Experience writing and improving runbooks, Experience leading incident response, Experience doing post-mortem analysis, Comfort working at the intersection of engineering and operations

Nice to Have

Multi-cloud experience across EKS, GKE, or similar, Observability-as-code experience, Familiarity with incident management platforms (incident.io or similar), Curiosity about how ML models are deployed and served at scale

What You'll Do.

Own the reliability of Baseten's multi-cloud Kubernetes infrastructure

Build and maintain observability infrastructure — metrics

and alerting — as code

and improve runbooks for recurring failure patterns

Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations

Diagnose and resolve runtime issues related to latency

and model lifecycle management

Define and instrument SLOs and SLIs across customer workloads and internal services

How You'll Work.

Team & Collaboration

Work closely with engineering, forward-deployed and product teams; Learn from recurring failure patterns; Turn tribal knowledge into automated mitigations; Raise the operational floor for the entire company

Full Job Description

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E https://www.baseten.co/blog/announcing-baseten-s-300m-series-e/, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As a Site Reliability Engineer at Baseten, you'll define and codify the gold standards of day 2 operations for our ML infrastructure platform. You'll envision and build robust systems, processes, automations, and observability tooling that keep our platform reliable at scale — and that empower the broader organization to operate confidently. You'll work closely with engineering, forward-deployed and product teams: learning from recurring failure patterns, turning tribal knowledge into automated mitigations, and raising the operational floor for the entire company. EXAMPLE INITIATIVES You'll work on projects like these as part of the SRE team: - Improve Baseten SRE Practices, by instrumenting SLOs and SLIs, improving alerting and observability for all services. - Building AI-assisted tooling for incident triage and response. RESPONSIBILITIES - Own the reliability of Baseten's multi-cloud Kubernetes infrastructure, including incident response, post-mortems, and remediation tracking. - Build and maintain observability infrastructure — metrics, logging, dashboards, and alerting — as code. - Author, validate, and improve runbooks for recurring failure patterns, ensuring they're structured for low-context, safe execution. - Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations. -

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