# [Junior / Senior / Staff] Software Engineer, Inference / Compute Infrastructure Engineering 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: $160K to $280K base salary per year (USD)
- Posted: 2026-07-16
- Apply by: 2026-10-08
- Apply: https://job-boards.greenhouse.io/togetherai/jobs/5186628007
- Page: https://www.1752.vc/careers/jobs/together-ai-junior-senior-staff-software-engineer-inference-compute-infrastructu/

## About the role

We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the...

## What they're looking for

- Strong software engineering background in Go, Python, Rust, or similar — you write and test real software for a living
- Experience with durable workflow orchestration tools such as Temporal, Cadence, or equivalent to run long-lived, manifest-driven workflows that survive failures and resume mid-execution
- Experience building software control planes or orchestration systems that model state and reconcile it over time (e.g., Kubernetes controllers/operators, custom reconciliation loops, workflow engines)
- Experience with event-driven systems — designing and building software around message queues, event streams, or pub/sub (e.g., Kafka, NATS, SQS) rather than polling or cron-driven scripts
- A product mindset. You’ve built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship

Tags: Engineering