Together AI · AI infrastructure

Senior or Staff Software Engineer, Inference / Compute Infrastructure Engineering

  • India (Remote)

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Still open on Together AI's site · checked just now

Level
Staff or principal
Posted

Senior or Staff Software Engineer, Inference / Compute Infrastructure Engineering

Together AI

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What you'll do

As written by Together AI · Read the original

Responsibilities

  • Build the provisioning state machine: design and implement the software that models the full lifecycle of a physical host from discovery, inference bring-up to GPU driver/CUDA stack, health validation, and decommission/RMA — as explicit, versioned states and transitions.
  • Build the self-service API: design declarative APIs and a control plane so the inference team can request, scale, and tear down inference clusters with one API call — no ticket, no human in the loop.
  • Automate self-healing: detect degraded or failed nodes, drain them safely, trigger repair or replacement, and reintroduce healthy capacity into the pool automatically.
  • Own reliability of the pipeline: idempotency, retries, rollback, and drift detection so the provisioning system is as dependable as any other production service.
  • Partner with the inference/ML platform team: understand the cluster shapes they need — topology, interconnect, scheduling constraints — and encode them as first-class abstractions in the platform.
  • Engineer it like software: strong typing, automated tests, code review, versioning, and CI/CD for infrastructure code — this is a product, not a collection of Ansible playbooks.

Requirements

Core requirements (all levels)

  • 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.

Nice to have

  • Exposure to bare-metal provisioning (PXE/iPXE, Redfish/IPMI, BMC) and/or networking fundamentals (VLANs, BGP, fabric design), or GPU/accelerator infrastructure.
  • Experience with GPU cluster software stacks (NCCL, CUDA, InfiniBand/RoCE).
  • Prior work at a hyperscaler, GPU cloud, or datacenter-scale infrastructure organization.
  • Systems programming in Rust or Go.

Skills

Stack

  • Python
  • Go
  • Rust
  • CUDA
  • Kubernetes

Working languages

English

Company

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