Technical Customer Success Engineer

ABOUT BASETEN

Baseten powers inference for the world's most dynamic AI companies, like OpenEvidence, Clay, Mirage, Gamma, Sourcegraph, Writer, Abridge, Bland, and Zed. 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. With our recent $150M Series D funding, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we’re scaling our team to meet accelerating customer demand.

The Role

You will serve as the primary post-sales technical owner for our most strategic customers, ensuring smooth deployment, performance, and reliability of ML workloads in production. You’ll own the technical success and long-term outcome of our strategic and enterprise accounts by managing and resolving escalations, maintaining and improving our runbooks, and proactively surface patterns that drive product improvements. This role blends hands-on debugging, infrastructure expertise, AI model performance monitoring, and executive-level customer-facing ownership. You’re of course not alone in this endeavor — partnering closely with product, engineering, and forward-deployed teams to remove technical friction, drive adoption, and ensure long-term success for high-value accounts.

Responsibilities

• Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, concurrency, and model lifecycle management.
  

• Debug infrastructure issues across Kubernetes (pods, controllers), networking, observability, and alerting systems.
  

• Lead incident response during outages or escalations, managing coordination between Product, FDE, Sales, and Engineering.

• Serve as the technical owner for top enterprise accounts with strict SLAs and high responsiveness expectations.
  

• Identify common failure modes and translate user feedback into roadmap signals, product improvements, our internal runbooks, knowledge bases, and diagnostic best practices.
  

• Own project coordination end-to-end: scoping, execution, communication, and stakeholder alignment across technical and non-technical teams ranging from feature requests, new deployments, and operational debugging issues.

Requirements

• Deep Kubernetes troubleshooting expertise, including advanced resource debugging, pod/runtime analysis, and log-based diagnostics using observability tooling such as Grafana, Loki, and Prometheus.
  

• Strong infrastructure debugging ability across container orchestration, networking, and service dependencies, with hands-on experience supporting production-grade clusters.
  

• Experience managing high-severity incidents with major customers, including SLAs, post-incident reviews, and clear communication throughout escalations.
  

• Proven project management and organizational skills with an ownership mindset, able to manage multiple complex, multi-stakeholder initiatives in parallel — including issue resolution, root-cause analysis, and feature delivery.
  

• Ability to translate recurring technical pain points into roadmap-level insights, documentation improvements, or product enhancements.
  

• Strong communication skills and executive presence during high-visibility situations, ensuring technical clarity and customer confidence.
  

• 3+ years of experience in a fast-paced, hig