Software Engineer, Platform, Tinker

About the Company

Thinking Machines Lab’s mission is to empower humanity through advancing collaborative general intelligence. We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open‑weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.

About Tinker Tinker is our fine‑tuning API that empowers researchers and developers to customize frontier AI to their needs — opening access to capabilities that have previously been concentrated in a handful of labs. We manage the infrastructure while allowing Tinkerers full flexibility in training open weights models with their own data, algorithms, and for their own needs. Tinker is rapidly adding new customers, features, and novel use‑cases.

We’re looking for a software engineer to own the platform systems that enable Tinker — billing and usage metering, permissions and access control, organizations and teams, data exports, audit logging, and the admin surfaces that tie them together. This role partners with everyone from product to legal, as every new feature, pricing change, and enterprise deal flows through your work.

• Design the authorization layer across all products: RBAC, API key scoping, organization hierarchies, and permission boundaries.
• Own billing infrastructure end‑to‑end, including usage metering and aggregation, plan management, payment processing, invoicing, and revenue recognition support.
• Build and evolve the organizations and teams model: seat management, SSO/SAML, workspace isolation, and invite flows.
• Implement data export and deletion pipelines that meet enterprise compliance and data residency requirements.
• Build audit logging so customers and internal teams have clear visibility into who did what, when.

Minimum qualifications:

Bachelor’s degree or equivalent experience in computer science, engineering, or similar. Proficiency in at least one backend language (Python or Rust). Experience with at least one of: billing/payments infrastructure, identity and access control (RBAC/ABAC, OAuth, SAML), or multi‑tenant platform systems. Thrive in a highly collaborative environment involving many, different cross‑functional partners and subject matter experts. A bias for action with a mindset to take initiative to work across different stacks and teams where you spot the opportunity to make sure something ships.

• 4+ years building backend systems in production.
• Experience building billing or metering systems at scale (Metronome pipelines, usage‑based pricing, invoicing pipelines).
• Familiarity with enterprise‑readiness patterns: SSO/SCIM provisioning, audit trails, data residency, custom contracts, role hierarchies.
• Strong opinions on building correct financial systems — idempotency, exactly‑once semantics, reconciliation.
• Experience with event‑driven architectures or stream processing for usage metering.
• Background in security engineering or a strong security mindset (least‑privilege design, secure defaults, threat modeling).
• Prior work at an AI/ML company, developer tools company, or API‑first platform.

This role is based in San Francisco, California.

Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.

We sponsor visas. While we can’t guarantee success for every candidate or role, if you’re the right fit, we’re committed to working through the visa process together.

Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

As set forth in Thinking Machines’ Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.