Staff AI Inference Infra Engineer - Compute Platform

United States Digital Space LLC; Amsterdam; On-site; EUR 110,000 - 170,000; Full time

Job summary

the company, a research-driven artificial intelligence organization, seeks a Software Engineer to build infrastructure-as-software that provisions hardware, brings it into service, and manages its full lifecycle, turning racks of GPUs into running inference clusters.

You will design state machines, declarative schemas, and CI/CD pipelines, transforming bare metal into AI clusters for training or inference with a product mindset and ownership.

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

Software engineering

Event-driven systems

Tools

Temporal

Cadence

Kafka

NATS

SQS

Job description

the company, a research-driven artificial intelligence organization, seeks a Software Engineer to build infrastructure-as-software that provisions hardware, brings it into service, and manages its full lifecycle, turning racks of GPUs into running inference clusters.

You will design state machines, declarative schemas, and CI/CD pipelines, transforming bare metal into AI clusters for training or inference with a product mindset and ownership.