AI Engineer

The Role

Baseten's Compute org is in hyper growth. As it scales, the systems and workflows that keep supply and demand balanced across our GPU fleet need to get more sophisticated, and this role exists to make sure they do.

Compute sits at the center of how Baseten allocates, forecasts, and manages the capacity that powers every customer inference request. The team that supports this work, C3, runs on a mix of internal tooling, manual processes, and systems that haven't fully kept pace with the scale of the problem. This role exists to close that gap.

You'll design, build, and ship AI-powered workflows that give the Compute and C3 teams real leverage, automating the manual, repetitive, and error-prone parts of the capacity lifecycle so the team can focus on judgment calls that actually need a human. We want someone who can walk in, audit what exists today, identify what's missing or broken, and start shipping fast.

You know when to reach for an existing internal tool and when to build something custom in Claude Code. You think two to three steps ahead about how the thing you build today fits into the broader capacity systems architecture tomorrow. And you bring a point of view on our stack, on what we should be building, and on where AI can do something existing tooling simply can't.

Responsibilities

• Ship AI-powered workflows for Compute and C3: build the agents and automations that give capacity analysts, ops leads, and engineers real leverage, off-loading manual and repetitive work like data pipeline cleanup, migration troubleshooting, and capacity investigation.
• Get insights in front of the team: turn fleet utilization, allocation, and demand-forecasting data into the dashboards, alerts, and recommendations that C3 and Compute leadership actually act on. A build isn't done until the team is using it.
• Audit the stack and generate your own backlog: Compute runs on a mix of tooling with real overlap and real gaps. Walk in with a point of view, identify what's missing or broken, and prioritize without waiting to be handed a roadmap.
• Ship team-productivity workflows fast: triage asks from Supply, Demand, and C3, find the low-hanging fruit, and build it. A good week looks like an ops lead asking for something Monday and having it live by Wednesday.
• Know when to go custom: not everything belongs in a point-and-click tool. Spin up bespoke AI-powered solutions in Claude Code when the problem calls for it, and make that call with judgment, not default.
• Think in systems, not solutions: every workflow you build has upstream and downstream implications across Supply, Demand, and Engineering. Anticipate them, design for them, and don't create technical debt someone else has to unwind six months later.
• Integrate third-party APIs and internal systems to sync events and information across disparate tools: ensuring data flows reliably between C3, the CRM, and the systems Compute depends on every day.
• Document what you build: if people can't find it, understand it, or trust it, it doesn't matter how well it works.

Requirements

• 3+ years of experience in AI/automation engineering, workflow automation, or a technical operations role, ideally at a high-growth, AI-native infrastructure or B2B company
• You've shipped production agents on Vercel. Build custom internal apps and agents on Vercel, with durable workflows and sandboxed execution, so what you ship runs reliably in production instead of as one-off scripts
• Genuine fluency with AI coding assistants and agent tooling (Claude Code, Cursor, Codex, or similar)
• Direct experience with a CRM or system-of-record platform (Salesforce or similar)
• A track record of owning end-to-end AI and automation workflows
• Proficiency with integration and automation platforms (n8n, Zapier, Make, Workato, or similar) and a fundamental understanding of APIs and webhooks
• Experience in high-growth technology companies, ideally in infrastructure, cloud, or operations-heavy environments

Nice to Have

• Familiarity with GPU infrastructure, capacity planning, or fleet management concepts
• Comfort building reporting and alerting on a data warehouse (BigQuery, Databricks) and BI layer (Sigma, Hex) - not as a data engineer, but as a consumer and builder on top of the data layer
• Experience building with agent platforms (Gumloop, n8n, Notion Agents, etc.) and/or agent frameworks (Vercel AI SDK, Claude Agent SDK, Mastra, etc.)
• Experience with high-stakes, operationally complex environments where mistakes have real business impact
• Challenging work and exposure to the operational core of a fast-scaling AI infrastructure company

Benefits

• Competitive compensation, including meaningful equity
• (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
• Paid parental leave
• Fertility and family-building stipend through Carrot
• (U.S. only) 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.