Customer Engineer

Customer Engineer 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 We're building a Customer Engineering team to own the post-sales technical relationship with our most strategic and enterprise customers. As a Sr. Customer Engineer, you'll be the technical front door for accounts running production ML workloads on Baseten — the person customers trust to keep their models healthy, their incidents short, and their roadmap heard. This role blends deep infrastructure debugging, AI/ML performance expertise, incident command, and proactive account ownership. You'll triage and resolve issues across Kubernetes, GPUs, networking, and model serving, lead war rooms during P0 escalations, and translate recurring pain points into product improvements. You're not just reactive — you'll monitor customer health, drive QBRs, set up proactive alerting, and identify expansion opportunities before customers have to ask. You'll partner closely with Solutions Architecture, SRE, Infra, Product, and Forward Deployed Engineering, but you own the customer outcome end-to-end: from first response to root-cause analysis to the follow-up that reinforces trust. RESPONSIBILITIES Technical Support & Debugging - Serve as the first responder to all post-sales customer issues via ticketing (Pylon) and Slack, triaging and resolving Tier 1 and Tier 2 issues independently. - Diagnose runtime issues related to latency, memory behavior, GPU utilization, concurrency, and model lifecycle management. - Debug infrastructure problems across Kubernetes (pods, controllers), networking, observability, and alerting systems. - Pull logs, read error traces, and correlate signals across Grafana, Loki, and Prometheus to pinpoint root causes — even when the real issue is buried layers deep. Incident Response & Escalation - Lead incident response during outages and escalations, coordinating across Product, SRE, Sales, and Engineering. - Own customer communication through resolution — even when the fix is handed off to SRE or Infra — including delivering root-cause analyses after every P0/P1. - Escalate to SRE/ other engineering teams with structured context (customer, affected models, what you've already ruled out, specific ask) so nothing gets lost in translation. - Drive post-incident alerting reviews: why did the customer find this before we did, and what instrumentation or process change prevents it next time? Proactive Account Ownership - Serve as the technical owner for top enterprise accounts with strict SLAs and high responsiveness expectations. - Set up and maintain proactive monitoring and alerts for all customer production models within 24 hours of handoff from SA(Solution Architect). - Drive the QBR process and proactive reengagement for expansion opportunities. - Track recurring failure patterns across accounts and push for durable fixes — not just incident closure. - Monitor internal feedback channels and route product-level issues to the right teams. Cross-Functional Collaboration - Own the SA-to-CE handoff for new customers: validate architecture, confirm production-readiness milestones, and establish escalation paths. - Maintain and improve runbooks, knowledge bases, and diagnostic best practices so the team scales with the customer base. - Translate user feedback into roadmap signals, documentation improvements, and product enhancements. - Coordinate ... (truncated, view full listing at source)