Member of Technical Staff, Enterprise Foundations

3 мес. назад

165k–240k USD / годСШАLeadHybrid

apisdkcli

Develop and own end-to-end backend features for enterprise AI foundations, addressing security, data privacy, billing, and deployment requirements for large-scale customers.

О компании

is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

Обязанности

Enterprise Foundations builds the capabilities the largest companies in the world need before they can run their business on . Global banks, insurers, healthcare and legal technology companies, and large-scale SaaS platforms are moving AI into production now, and they arrive with requirements that only apply to scaled companies: how their organization and users are modeled, who is allowed to do what, how usage is metered and billed, what gets logged, where data lives and who holds the keys, and whether the whole thing can run inside their own cloud.
You will own that work as end-to-end features. A single project routinely starts in a customer conversation, becomes a change to a core data model or API, and then has to be threaded through the control plane, the training and inference stacks, the SDK and CLI, and the console before it counts as shipped. Much of what we build is a foundational shift rather than an addition: a new primitive that other teams' code has to move onto, rolled out against live production traffic without breaking anyone.
The work sits close to revenue. Requirements come out of live enterprise deals, security reviews, and customer conversations. You will be in those rooms, decide what product becomes, and go build it.
Own foundational capabilities end to end — data model and API through control plane, runtime, SDK/CLI, and console — and migrate live systems onto them
Design the primitives large customers organize around — organizations and sub-accounts, groups, roles, service identities — and connect them to enterprise directories through federation and provisioning (SSO, SCIM)
Design multi-tenant authorization, policy enforcement, and audit systems that hold up in front of a security architect
Make usage metering, spend controls, and billing correct and legible at scale — customers reconcile our numbers against their own
Own data isolation and key management — customer-managed encryption keys across AWS, GCP, and Azure — threaded through datasets, fine-tuning, RL, checkpoints, models, and inference
Deploy and operate inside a customer's own cloud, and solve data residency and regional isolation for customers with hard constraints
Use AI tooling aggressively — we expect you to automate yourself

Требования

4+ years building and operating production backend or distributed systems at scale
Strong server-side engineering skills in Go, Python, C++, TypeScript, or similar, and willingness to work outside your primary layer to land a feature
Experience designing APIs and data models that other teams build on, and evolving them under live traffic without breaking callers
Hands-on depth in at least one major cloud (AWS, GCP, or Azure): IAM and workload identity, KMS, object storage, and VPC networking
A track record of owning an ambiguous, cross-team workstream from requirement through production
Willingness to work directly with customers

Будет плюсом

Enterprise identity and tenancy: SSO, SCIM provisioning, RBAC/ABAC, audit logging, and org modeling
Metering, quotas, or billing systems where correctness is customer-visible
Applied cryptography and key management: envelope encryption, KMS, and threat modeling
Kubernetes depth and infrastructure-as-code fluency (Terraform, GitOps)
Familiarity with LLM inference and fine-tuning — our work runs straight through the training and serving stacks, so it helps

Другое

You want your work measured in unblocked revenue, not tickets closed
You're comfortable owning domains you've never worked in before
You want the whole problem — data model through UI — and don't need someone else to draw the edges for you
You can hold your own with an enterprise security architect
You'd rather ship what closes the deal than perfect the abstraction
You treat ambiguity as the job, not a complaint about the job