Senior Platform Engineer, Inference & GPU Compute Infra

Together; San Francisco (CA); On-site; USD 240,000 - 280,000; Full time

Benefits offered by this job

Startup equity

Health insurance

Job summary

Together AI is seeking a Staff Software Engineer to build systems that treat infrastructure as software, turning racks of GPUs into running inference clusters via a declarative manifest-driven platform. You’ll design engines to materialize clusters, with a focus on automation, reliability, and a product mindset.

You will own provisioning state machines, self-service APIs, and end-to-end lifecycle management, from discovery to decommission, while ensuring production-grade quality and CI/CD

Qualifications

• 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.

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.

Skills

Go

Python

Rust

Temporal

Cadence

Kubernetes

Event-driven design

Product mindset

Tools

Temporal

Cadence

Kafka

Job description

Together AI is seeking a Staff Software Engineer to build systems that treat infrastructure as software, turning racks of GPUs into running inference clusters via a declarative manifest-driven platform. You’ll design engines to materialize clusters, with a focus on automation, reliability, and a product mindset.

You will own provisioning state machines, self-service APIs, and end-to-end lifecycle management, from discovery to decommission, while ensuring production-grade quality and CI/CD