Baseten Logo

Baseten

AI Engineer

Posted 11 Days Ago
Hybrid
San Francisco, CA, USA
175K-190K Annually
Mid level
Hybrid
San Francisco, CA, USA
175K-190K Annually
Mid level
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.
The summary above was generated by AI

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).

HQ

Baseten San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

2 Days Ago
Hybrid
San Jose, CA, USA
230K-286K Annually
Senior level
230K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Design, develop, deploy, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize model performance, scalability, latency, throughput, hardware utilization, and cost. Architect multi-model orchestration pipelines, lead technical governance and design reviews, define AI engineering standards, and mentor senior technical staff.
Top Skills: AWSAws UltraclustersAzureC#C++CudaGoGCPHugging FaceJavaPythonPyTorchScalaVectordbs
2 Days Ago
Hybrid
2 Locations
197K-246K Annually
Mid level
197K-246K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Designs, develops, deploys, and supports large-scale AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. The role optimizes AI infrastructure for scalability, latency, throughput, cost, and hardware utilization; defines reliability objectives; leads architecture and technical reviews; and mentors engineering staff.
Top Skills: AWSAws UltraclustersAzureC#C++CudaGoGCPGpuHugging FaceJavaPythonPyTorchScalaTpuVector Databases
2 Days Ago
Hybrid
San Jose, CA, USA
230K-286K Annually
Senior level
230K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Design, develop, deploy, and optimize foundational AI systems, including large language model inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture, cost-performance optimization, technical standards, and design reviews for scalable production AI systems. Mentor senior technical staff and contribute to the long-term roadmap for responsible AI infrastructure.
Top Skills: AWSAzureC#C++CudaGoGCPHugging FaceJavaLarge Language ModelsMulti-Agent SystemsPythonPyTorchRetrieval-Augmented GenerationScalaSimilarity SearchVector Databases

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account