Member of Technical Staff, Enterprise Foundations
Fireworks AI2 days ago
Base Salary
$165k - $185k/yr
Responsibilities
- Own foundational capabilities end to end across data models, APIs, control-plane services, runtimes, SDKs, CLIs, and the console.
- Design organization, sub-account, group, role, and service-identity primitives and connect them to enterprise directories through federation and provisioning.
- Build multi-tenant authorization, policy enforcement, and audit systems suitable for enterprise security requirements.
- Develop accurate, customer-visible usage metering, spend controls, and billing systems at scale.
- Own data isolation and customer-managed encryption keys across AWS, GCP, and Azure for datasets, fine-tuning, reinforcement learning, checkpoints, models, and inference.
- Deploy and operate Fireworks inside customers’ clouds while solving data-residency and regional-isolation requirements.
- Migrate live production systems onto foundational primitives without breaking existing users or callers.
- Use AI tooling to automate development and operational work.
Requirements
- At least 2 years of experience building and operating production backend or distributed systems at scale.
- Strong server-side engineering skills in Go, Python, C++, TypeScript, or a similar language, with willingness to work across layers.
- Experience designing APIs and data models used by other teams and evolving them safely under live production traffic.
- Hands-on depth with at least one major cloud provider, including IAM, workload identity, KMS, object storage, and VPC networking.
- Track record of owning ambiguous, cross-team workstreams from requirements through production.
- Willingness to work directly with customers and communicate effectively with enterprise security architects.
- Preferred experience building for regulated enterprises, including SOC 2 and customer security reviews.
- Preferred experience with SSO, SCIM provisioning, RBAC/ABAC, audit logging, organization modeling, metering, quotas, billing, applied cryptography, envelope encryption, and threat modeling.
- Preferred Kubernetes experience and infrastructure-as-code fluency with Terraform and GitOps.
- Familiarity with LLM inference and fine-tuning, including training and serving stacks, is preferred.
Benefits
- Work on foundational AI infrastructure for enterprise customers.
- Collaborate with world-class engineers and AI researchers.
- High ownership, direct customer impact, and work closely connected to revenue.
- Equal-opportunity and inclusive workplace.