S Software Engineer - Partner Platform San Francisco (Remote), CA, US Mid machine learning agent distributed systems

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Software Engineer - Partner PlatformFull Time computer Remote location\\_on San Francisco (Remote), CA, US Midopen\\_in\\_new Apply on site Opens in a new tab on website.## Job DescriptionABOUT BASETENBaseten 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 ROLEThe AI ecosystem is being built by many companies at once: model labs creating increasingly capable models, hyperscalers providing infrastructure and distribution, developers building new AI products, and a growing ecosystem of tools that agents can use.Baseten sits at the center of that ecosystem as the inference platform developers use to run AI in production. Partner Engineering is how we connect those worlds.As one of the first engineers focused on Partner Engineering at Baseten, you'll build the technical foundation behind some of our most strategic relationships. You'll work directly with engineers at leading model labs, hyperscalers, developer platforms, and AI infrastructure companies to turn partnerships into products developers can actually use.You don't need a previous partner engineering title. We want an engineer who enjoys working directly with another company's technical team and carrying the resulting product decisions into production at Baseten.WHAT YOU'LL BUILD- Bring new capabilities into Baseten. Integrate a search or developer-tools provider into Baseten so an agent can call the service during inference, with consistent authentication, execution, failure handling, observability, and usage reporting.- Take Baseten into new distribution channels. Integrate Baseten with a hyperscaler, cloud marketplace, or developer platform so customers can discover models, provision access, and run inference through a partner's product while Baseten handles the underlying serving infrastructure.- Launch models with leading model labs. Build the infrastructure that lets developers discover and run a model lab's newest models on Baseten, including access controls, usage attribution, metering, and the systems required to support commercial agreements such as revenue sharing.- Create the partner platform itself. Identify the primitives common across these integrations and turn them into reusable platform capabilities so we can launch increasingly sophisticated partnerships without reinventing the stack every time.WHAT YOU'LL OWN- Lead strategic partner integrations from technical discovery and architecture through implementation, launch, and production operation.- Work directly with partner engineering teams to design APIs, define system boundaries, resolve cross-company dependencies, and make architectural decisions.- Write substantial production code and own the systems you build.- Build reusable partner-platform primitives across identity, provisioning, inference, model serving, metering, billing, and other Baseten platform capabilities.- Own technical delivery across Baseten and partner teams, including milestones, dependencies, risks, and architectural tradeoffs.- Work closely with Partnerships and Product to understand where the ecosystem is going and translate emerging opportunities into platform investments.- Raise the bar for integration reliability through strong API contracts, testing, observability, safe rollouts, and thoughtful failure handling.- Help define what Partner Engineering becomes at Baseten as both the team and our ecosystem grow.REQUIREMENTS- Experience designing, shipping, and operating large-scale distributed systems in production. You can explain the architectural choices you made and how they meet customers' needs at scale.- A record of leading ambiguous engineering projects across teams while contributing substantial production code yourself.- Sound judgment about API design, service boundaries, and failure handling. You've built systems that uphold API contracts and meet measurable service-level objectives that customers and partners depend on.- Experience turning requests from customers, partners, or other engineering teams into a defined technical scope. You can explain a constraint, propose an alternative, and document the decision.- Comfort working across application code and cloud infrastructure, including debugging behavior that crosses service boundaries.NICE TO HAVE- Product integrations with cloud providers, developer platforms, or other infrastructure companies.- Usage metering, marketplace infrastructure, or commerce systems that support relationships among multiple parties.- Model serving or other artificial intelligence (AI) infrastructure used in production.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, nationa## Skills & Technologiesmachine learningagentdistributed systems
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