Original listing text, shown exactly as published by the company.
THE ROLE
As Senior Manager of Cloud Platform and Site Reliability, you will lead and grow the org responsible for the infrastructure that powers Baseten's machine learning platform. This is a manager-of-managers role: you will lead team leads across our Cloud Platform and Site Reliability Engineering functions, setting the technical direction, defining reliability standards, and building the organizational muscle to scale our infrastructure alongside the product.
You will own the end-to-end health of our cloud infrastructure and SRE practice — from coaching your leads through complex incident response and enterprise customer escalations, to shaping the multi-year roadmap for multi-cloud capacity, GPU inference infrastructure, and observability platforms. You operate at the intersection of people, strategy, and systems: you know how to build and develop strong teams, hold a high bar for engineering excellence, and make principled tradeoffs between long-term investment and short-term operational demands.
This role requires someone who can zoom out to set org-level direction while remaining technically credible enough to engage meaningfully in architectural decisions across Kubernetes, multi-cloud infrastructure, and reliability engineering.
RESPONSIBILITIES
- Lead, grow, and develop team leads across the Cloud Platform and Site Reliability Engineering orgs, building a culture of ownership, technical excellence, and continuous improvement.
- Set the technical direction and roadmap for infrastructure, reliability, and platform engineering at the org level — balancing near-term operational needs with long-term strategic investments.
- Own the reliability posture of the platform end-to-end, establishing and enforcing org-wide standards for SLOs/SLIs, incident response, observability-as-code, runbooks, and post-incident reviews.
- Drive cross-functional collaboration with product, engineering, and customer-facing teams to ensure infrastructure capabilities and reliability investments align with product goals and enterprise customer requirements.
- Oversee incident management and escalation processes for high-severity production issues, ensuring clear communication, rapid resolution, and systemic follow-through.
- Translate recurring operational pain points and customer feedback into roadmap priorities, product improvements, and runbook enhancements across both teams.
- Ensure best practices for CI/CD, infrastructure-as-code, GitOps, Kubernetes, and cloud resource management are consistently adopted and maintained across the org.
- Partner with forward-deployed and customer success teams to support enterprise accounts with strict SLAs and complex infrastructure requirements.
- Navigate ambiguity and make sound architectural and organizational tradeoffs, avoiding unnecessary complexity while enabling your teams to move fast.
- Demonstrate accountability, pride of ownership, and high standards — and expect the same from your leads and their teams.
REQUIREMENTS
- Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or a related field.
- Proven experience managing managers and leading multiple high-performing infrastructure, platform, or SRE teams in a fast-paced, high-growth environment.
- Deep technical expertise in Kubernetes (multi-cloud across EKS, GKE, or similar), cloud infrastructure, and distributed systems, with the ability to engage credibly in architectural and operational decisions.
- Hands-on background with infrastructure-as-code (e.g., Terraform, Pulumi) and CI/CD tooling (e.g., GitHub Actions, GitLab CI, Jenkins); familiarity with GitOps workflows (e.g., Flux CD, ArgoCD, Helm).
- Strong foundation in observability tooling — metrics (Prometheus, VictoriaMetrics), logging (Loki, ELK), dashboards (Grafana), tracing (OpenTelemetry) — and a track record of raising reliability standards through SLOs, SLIs, and observability-as-code.
- Experience owning incident management and enterprise SLAs at scale, including executive-level communication during high-severity incidents and rigorous post-incident follow-through.
- Demonstrated ability to lead complex, multi-stakeholder technical initiatives from scoping through execution, balancing engineering excellence with pragmatic delivery.
- Strong communication skills with executive presence, capable of representing technical work clearly to both technical and non-technical audiences.
- No prior machine learning experience required, but should be open to learning about ML infrastructure and model serving.
BONUS
- Familiarity with running high-performance AI models and workloads, including troubleshooting ML pipelines from preprocessing through inference and serving.
- Experience with GPU infrastructure, including fractional GPU provisioning and multi-node model serving (e.g., on H100s or B200s).
- Experience with incident management platforms (e.g., incident.io, PagerDuty) and building AI-assisted tooling for incident triage and response.
- Experience scaling an SRE practice: defining runbook standards, building self-healing automations, and converting high-frequency failure patterns into systematic mitigations.
