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 end-to-end on projects spanning feature requests, new deployments, and operational debugging — scoping, execution, communication, and stakeholder alignment.

REQUIREMENTS:

• Deep Kubernetes troubleshooting expertise, including resource debugging, pod/runtime analysis, and log-based diagnostics with observability tooling (Grafana, Loki, Prometheus).

• Strong infrastructure debugging across container orchestration, networking, and service dependencies, with hands-on production cluster experience.

• Experience managing high-severity incidents with major customers — SLAs, war rooms, post-incident reviews, and clear executive-level communication throughout.

• Proven project management skills with an ownership mindset: you can run multiple complex, multi-stakeholder initiatives in parallel without dropping threads.

• Ability to translate recurring technical pain points into roadmap-level insights and product improvements.

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

• 3+ years of experience in a fast-paced, high-growth, or customer-facing engineering environment.

NICE TO HAVE:

• Familiarity with high-performance AI model serving, including troubleshooting ML pipelines from preprocessing through inference.

• Experience with ticketing and incident-response platforms such as Pylon or Zendesk.

• Hands-on experience with Helm, Flux, CI/CD tooling, or scripting automations for deployment and operational workflows.

• Background in SRE, DevOps, or forward-deployed engineering roles at an infrastructure company.

BENEFITS:

• Competitive compensation, including meaningful equity.

• 100% coverage of medical, dental, and vision insurance for employee and dependents

• Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)

• Paid parental leave

• Company-facilitated 401(k)

• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.

At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).