# (Staff / Senior Staff) AI Inference Reliability Engineer, Compute Infra at Together AI

- Company: Together AI
- What the company does: Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research. Backed by General Catalyst, Kleiner Perkins and NEA.
- Company website: https://www.together.ai/
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco
- Work setup: On-site
- Pay: $250K to $320K base salary per year (USD)
- Posted: 2026-10-20
- Apply by: 2026-12-04
- Apply: https://job-boards.greenhouse.io/togetherai/jobs/5266079007?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/together-ai-staff-senior-staff-ai-infra-engineer-inference-infrastructure/

## About the role

We're looking for a software engineer, reliability-minded but still a builder, to own what happens in production to the Kubernetes-native control plane that provisions and runs our GPU inference fleet. The platform team builds the manifest-driven API and controllers that let the inference team declare what they need, a cluster, a model deployment, a capacity change, and get it reconciled underneath. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- Deep experience owning production reliability for large-scale distributed systems, GPU/ML-serving infrastructure experience is a strong plus
- Familiarity with the operational realities of multi-tenant model serving (LoRA/adapter-based serving) and with running differentiated SLOs across model pools of different priority
- A demonstrated track record of eliminating operational toil through automation and tooling you built yourself, not just process or documentation
- Hands-on experience with Kubernetes controller/CRD patterns, reconciliation loops, and node-level health/remediation systems
- Comfort with event-driven architectures, backpressure/circuit-breaking design, and treating observability (metrics, logs, traces) as something built into a system, not added after an incident
- A software-engineering mindset first: you write and ship production code, and you think about GPU infrastructure as software to be engineered, not a fleet to be manually operated

Tags: Engineering

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/together-ai-staff-senior-staff-ai-infra-engineer-inference-infrastructure/