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What You’ll Do:

The Physical AI Engineering Team at CoreWeave is building the software and infrastructure that enables demanding AI, simulation, robotics, and engineering workloads to run reliably at scale.

As these workloads become more complex, the challenge is no longer simply providing compute. We need to make heterogeneous workloads easier to execute, observe, reproduce, and move across different systems without hiding the capabilities or semantics of the infrastructure underneath them.

About the role:

We’re seeking a Staff Software Engineer, Runtime Systems to help design and build this layer.

This is a hands-on systems engineering role at the intersection of distributed systems, runtimes, workflow execution, programming language concepts, and large-scale compute infrastructure.

You’ll work on the foundations that allow complex workloads to move from an abstract description into reliable execution across systems such as Kubernetes, Argo, OSMO, and future execution environments.

A major part of the role is deciding where abstraction is useful — and where it creates more complexity. Rather than building another universal workflow engine, you’ll help establish clear contracts between our platform and the systems that execute work, while preserving native capabilities.

You’ll operate across architecture and implementation: defining contracts, writing production software, validating assumptions against real workloads, and working closely with platform and infrastructure teams.

In this role, you will:

• Runtime Systems & Architecture
• Design and build runtime components for complex AI, simulation, and engineering workloads.
• Define abstractions for workloads, execution environments, dependencies, state, capabilities, and failure.
• Design interfaces between higher-level services and systems such as Kubernetes, Argo, and OSMO.
• Establish clear boundaries around which systems own state, decisions, and side effects.
• Make architectural decisions balancing simplicity, extensibility, performance, and operational reality.
• Execution Models & Contracts
• Define durable contracts between workload definitions, control-plane services, and execution backends.
• Develop typed representations and schemas that allow workloads to be transformed safely across systems.
• Design compatibility and evolution mechanisms for those contracts.
• Build conformance and validation mechanisms that make guarantees executable rather than dependent on documentation.
• Reason deeply about retries, partial failure, idempotency, cancellation, dependencies, and uncertain outcomes.
• Hands-On Systems Engineering
• Write production-quality software for critical runtime and control-plane components.
• Build adapters and integrations for heterogeneous execution environments.
• Diagnose behaviour across application, orchestration, cluster, and infrastructure boundaries.
• Improve the reliability, observability, and debuggability of distributed workload execution.
• Work closely with Go, Kubernetes, and infrastructure engineers to turn architecture into production systems.
• Performance & Experimentation
• Develop rigorous ways to understand workload performance across large-scale GPU infrastructure.
• Design experiments that separate real performance gains from noise, warm-up effects, scheduling behaviour, and stragglers.
• Build repeatable workload and benchmark environments.
• Use evidence from real execution to challenge assumptions and guide platform development.
• Technical Leadership
• Lead ambiguous systems problems where the correct architecture is not yet known.
• Reduce complex problems into smaller contracts and mechanisms that can actually be implemented.
• Challenge unnecessary abstraction and simplify designs where complexity has outgrown its value.
• Influence technical direction across teams without requiring direct authority.
• Mentor engineers and contribute to technical hiring and engineering standards.

Who You Are:

• Significant experience building complex systems software, distributed infrastructure, runtimes, workflow systems, or adjacent technology.
• Deep expertise in at least one of:
• Distributed systems
• Runtime systems
• Workflow or execution engines
• Programming languages, compilers, or interpreters
• Cluster scheduling and orchestration
• High-performance or systems software
• Strong software engineering fundamentals and production coding ability.
• Experience designing APIs, protocols, schemas, or contracts between independently evolving systems.
• Strong understanding of distributed-system failure modes, state, authority, retries, concurrency, and side effects.
• Strong technical judgement around when abstraction helps and when it simply moves complexity elsewhere.
• Comfortable entering unfamiliar technical domains and building depth quickly.
• Strong communication skills and experience influencing architectural decisions across teams.

Experience with some of the following would be valuable, but is not required:

• Go, Rust, C/C++, or Python.
• Kubernetes and containerised infrastructure.
• Argo, OSMO, Temporal, Ray, Kubeflow, or similar systems.
• GPU clusters or large-scale AI infrastructure.
• High-performance computing.
• Simulation, robotics, autonomous systems, or Physical AI.
• Programming language or compiler research.
• Performance engineering.
• Cloud infrastructure at scale.
• Platforms designed to be operated by autonomous software or AI agents.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team:

• Systems Thinker: You ask where authority lives, what guarantees actually exist, and what happens when systems fail.
• Technically Deep: You want to understand how systems really behave, not just how they are supposed to behave.
• Pragmatic: You value elegant engineering, but care more about whether it works for real workloads.
• Evidence-Driven: You test assumptions and change direction when the evidence says you should.
• Strong Technical Leader: You can form a view, challenge senior stakeholders, and bring others with you.
• Commercially Aware: You understand that technical decisions need to improve customer outcomes, engineering velocity, reliability, or economics.
• Ownership Mentality: You take responsibility for getting difficult systems into production.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast. We’re in an exciting stage of hyper-growth, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support entrepreneurial thinking, independent judgement, and collaboration. You’ll work alongside some of the best talent in the industry on technically difficult problems at the frontier of AI infrastructure.

The base salary range for this role is 116,000 GBP to 155,000 GBP. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).