Backend Engineer (AI Infrastructure)

Location: New York, United States; hybrid work

Salary: $165,000–$185,000 per year plus equity

Company

hirify.global provides a platform for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.

What you will do

• Own foundational enterprise capabilities end to end, from data models and APIs through control plane, runtime, SDK/CLI, and console.
• Design organization, sub-account, group, role, and service-identity primitives with SSO and SCIM federation and provisioning.
• Build multi-tenant authorization, policy enforcement, audit, metering, spend-control, and billing systems.
• Own data isolation and customer-managed encryption keys across AWS, GCP, and Azure, spanning datasets, fine-tuning, reinforcement learning, checkpoints, models, and inference.
• Deploy and operate hirify.global inside customer clouds while addressing data residency and regional isolation requirements.
• Work directly with enterprise customers and coordinate ambiguous, cross-team features through production rollout.

Requirements

• 2+ years 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 flexibility to work across layers.
• Experience designing and evolving APIs and data models under live production traffic.
• Hands-on experience with AWS, GCP, or Azure, including IAM, workload identity, KMS, object storage, and VPC networking.
• Ownership of ambiguous cross-team workstreams from requirements through production and willingness to work directly with customers.

Nice to have

• Experience with regulated enterprises, SOC 2, and customer security reviews.
• Enterprise identity and tenancy systems, including RBAC/ABAC and audit logging.
• Metering, quotas, billing, applied cryptography, envelope encryption, or threat modeling.
• Kubernetes, Terraform, GitOps, or familiarity with LLM inference and fine-tuning.

Culture & Benefits

• Work on AI infrastructure, including low-latency inference and scalable model serving.
• Collaborate with engineers and AI researchers on emerging technologies.
• Emphasis on ownership, direct impact, and shipping results with minimal bureaucracy.
• Equity is included in the compensation package.
• Inclusive, equal-opportunity work environment.