Software Engineer, Compute Infrastructure

Alpaca Research; Cambridge (MA); On-site; USD 180,000 - 260,000; Full time

Job summary

Alpaca Research is building the compute infrastructure for next‑gen AI research. We’re hiring a Software Engineer, Compute Infrastructure to own and maintain core systems that power researchers and models, focusing on speed, reliability and security as the platform scales.

You will work across Kubernetes, cloud VMs and on‑prem machines, collaborating with researchers and engineers to improve tooling, performance, and fault tolerance while keeping security and observability at the forefront.

Qualifications

• Strong systems engineering fundamentals and experience shipping production services in Rust, or the ability to become fluent quickly.
• Experience building or operating schedulers, distributed control planes or job orchestration systems.
• Hands‑on cloud infrastructure experience on AWS or GCP: compute, GKE/EKS, IAM and quotas.
• A habit of measuring: profiling, load testing, and stating claims with numbers.
• Care for correctness: state machines, idempotency, failure handling, and tests that try to break your own code.
• Hands‑on fluency with AI coding agents, and good judgment about when to trust their output.
• Clear writing for design docs, runbooks and decisions.

Responsibilities

• Own production systems. Operate and maintain distributed backend services end to end. Debug hard production problems and be a first responder when things break.
• Improve performance. Profile, load-test and optimise services and databases under heavy concurrent load, and back every change with measurements.
• Build for reliability. Design for failure: retries, idempotency, recovery and consistency under partial outages. Test it with fault injection and simulation.
• Work across compute environments. Kubernetes, cloud VMs and on‑prem machines, across various hardware configurations.
• Keep it secure. Own access control, least‑privilege permissions and cost guardrails.
• Support internal users. Work closely with researchers and engineers to understand their needs and improve their experience with the tools you maintain.

Skills

Rust

Schedulers

Distributed systems

Cloud infrastructure

AI tooling

Documentation

Tools

AWS

GCP

Kubernetes

IAM

Job description

Who we are

Today, AI is something you rent. Alpaca is building the full stack of hardware, software, models, and applications together to make it something you own.

We are developing a new computer architecture that breaks the economics keeping frontier models trapped in datacenters. On top of that, we’re building a platform of models, applications, and services that give that hardware meaning.

Personal AI is moving from the datacenter to the desk, and we are driving that change.

Our team is based in Cambridge, MA.

Software Engineer, Compute Infrastructure

You will own and maintain core infrastructure that our research depends on, keeping it fast, reliable and secure as the company grows.

In This Role You Will

• Own production systems. Operate and maintain distributed backend services end to end. Debug hard production problems and be a first responder when things break.

• Improve performance. Profile, load-test and optimise services and databases under heavy concurrent load, and back every change with measurements.

• Build for reliability. Design for failure: retries, idempotency, recovery and consistency under partial outages. Test it with fault injection and simulation.

• Work across compute environments. Kubernetes, cloud VMs and on‑prem machines, across various hardware configurations.

• Keep it secure. Own access control, least‑privilege permissions and cost guardrails.

• Support internal users. Work closely with researchers and engineers to understand their needs and improve their experience with the tools you maintain.

What We Hope You’ll Bring

• Strong systems engineering fundamentals and experience shipping production services in Rust, or the ability to become fluent quickly.

• Experience building or operating schedulers, distributed control planes or job orchestration systems.

• Hands‑on cloud infrastructure experience on AWS or GCP: compute, GKE/EKS, IAM and quotas.

• A habit of measuring: profiling, load testing, and stating claims with numbers.

• Care for correctness: state machines, idempotency, failure handling, and tests that try to break your own code.

• Hands‑on fluency with AI coding agents, and good judgment about when to trust their output.

• Clear writing for design docs, runbooks and decisions.

Bonus Points

• Running GPU fleets at scale: drivers, NCCL, high-speed interconnects, spot capacity.

• Experience with Kueue, JobSet or other batch scheduling on Kubernetes.

• Experience building infrastructure for ML research teams.