AI Engineer

Posted 12 Days Ago
San Francisco, CA, USA
Hybrid
175K-190K Annually
Mid level
Software
Inference will be the largest market ever created.
The Role
Build and deploy AI-powered workflows, agents, automations, dashboards, alerts, and recommendations for Compute and C3 capacity operations. Integrate CRMs, internal systems, and third-party APIs; automate repetitive operational processes; troubleshoot data and migrations; audit existing tooling; and prioritize new solutions. The role requires end-to-end ownership, rapid production delivery, strong systems thinking, and fluency with AI coding assistants, workflow platforms, APIs, and webhooks.
Summary Generated by Built In

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).

Skills Required

  • 3+ years of experience in AI/automation engineering, workflow automation, or technical operations
  • Experience shipping production agents on Vercel
  • Experience building custom internal apps and agents on Vercel with durable workflows and sandboxed execution
  • Fluency with AI coding assistants and agent tooling such as Claude Code, Cursor, or Codex
  • Direct experience with Salesforce or a similar CRM/system-of-record platform
  • Track record of owning end-to-end AI and automation workflows
  • Proficiency with n8n, Zapier, Make, Workato, or similar integration and automation platforms
  • Fundamental understanding of APIs and webhooks
  • Experience at high-growth technology companies, ideally in infrastructure, cloud, or operations-heavy environments
  • Familiarity with GPU infrastructure, capacity planning, or fleet management
  • Experience building reporting and alerting on data warehouses such as BigQuery or Databricks and BI tools such as Sigma or Hex
  • Experience with agent platforms or frameworks such as Gumloop, n8n, Notion Agents, Vercel AI SDK, Claude Agent SDK, or Mastra
  • Experience in high-stakes, operationally complex environments

Baseten Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Baseten and has not been reviewed or approved by Baseten.

  • Fair & Transparent Compensation Feedback suggests pay targets the top of market with explicit ranges in postings and a stated aim to provide 90th percentile salaries with equity. Role descriptions emphasize competitive, experience-based pay bands and meaningful stock grants.
  • Healthcare Strength Healthcare is described as fully covered for medical, dental, and vision for employees and their families, reducing out-of-pocket costs. This comprehensive coverage is consistently highlighted alongside other core benefits.
  • Leave & Time Off Breadth Time off policies include unlimited PTO with a minimum expectation of at least four weeks, 16 paid company holidays, and a company-wide winter break. These elements indicate substantial protected time away from work.

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The Company
HQ: San Francisco, CA
350 Employees
Year Founded: 2019

What We Do

AI’s future won’t be a few massive models built by a handful of labs. It’ll be millions of specialized models embedded into every product, workflow, and experience by the people closest to the customer. The foundation of that future is inference. Inference determines the performance, reliability, latency, and economics of every AI product. For AI to scale globally, it must be as reliable, fast, cost-effective, and high-quality as possible. That’s why Baseten exists. Companies like Abridge, Cursor, Lovable, Notion, and OpenEvidence depend on Baseten to power mission-critical AI workloads in production.

Why Work With Us

We’re an interdisciplinary team of researchers, engineers, and operators building the Inference Cloud our AI future demands. We’re running at a hard systems problem that requires first-principles thinking across the entire stack. The bar is high. We work hard, move fast, and care deeply about quality.

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