AI Engineer
Baseten is hiring an AI Engineer for a remote role open to applicants in United States. It pays $175k-$190k a year and Level rates it ; you can apply on Baseten.
Level's read on this job
- Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions Claude, Vercel AI SDK and Databricks among its tools and skills.
- Level classes it as a mid-level role.
- Baseten has 103 other open roles on Level.
AI in this role
Design and ship AI-powered agents and workflows to automate compute capacity management and infrastructure operations.
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 $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
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.
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).
How we rate this
AI Engineer at Baseten rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $175k
- Typical AI engineer job
- $184k
This posting starts 5% below the typical AI engineer job. See AI engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where automation was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where python was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, AI agents, Automation, Data Pipelines, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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