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About the Role

We are seeking a Senior AI Engineer to build the agentic layer of our Physical AI platform. You will design, build, and ship the agents behind our engineering copilot, systems that take a real engineering problem, explore data, build and evaluate models, and return actionable results. This is a hands-on engineering role focused on turning research into reliable production systems.

Responsibilities

Design and build agents that run the auto-research loop on customer engineering problems: data exploration, feature and model iteration, evaluation and reporting.
Define tool interfaces and MCP servers that expose platform capabilities to agents in a safe and predictable way.
Own context and memory design for long-running agent tasks, including retrieval over engineering data, documentation and past experiments.
Select and integrate models, balancing quality, latency and cost.
Build evaluation harnesses and benchmarks that measure agent performance on real engineering use cases.
Instrument agents with tracing and observability and use that data to improve them.
Design guardrails, sandboxed code execution, permission models and human-in-the-loop checkpoints for agent safety.
Take agents from prototype to production: testing, CI/CD, deployment, monitoring and on-call ownership.
Contribute to ML work alongside ML Engineers – model training, evaluation and Physical AI library development.
Translate the vocabulary and workflows of physical engineering domains into agent behaviour.
Cover ML engineering work when needed, and help ML Engineers adopt agentic tooling.
Work with Research to turn promising agentic approaches into production systems.
Partner with platform engineers on the agent runtime, workflow orchestration and auth.
Work with Frontend and Product to expose agent capabilities in the product.
Mentor engineers, and interview and onboard new team members.

Requirements

5+ years of professional software engineering experience.
2+ years building production systems on top of LLMs.
Shipped at least one agentic system to production with real users.
Strong production Python.
Hands-on experience with LLM APIs and agent frameworks.
Experience designing tools and APIs for agents, including MCP or equivalent tool-calling protocols.
Experience building evaluation for LLM or agent systems.
Solid ML fundamentals: ability to train and evaluate models with scikit-learn or PyTorch, understanding validation, overfitting and uncertainty.
Experience with retrieval and context engineering for agents.
Strong software engineering practices: code review, automated testing, CI/CD, observability, Docker and Kubernetes.
Experience with at least one major cloud provider (AWS preferred).
Security-minded: sandboxing, authentication/authorisation, prompt injection and data isolation in multi-tenant systems.
Clear technical communication with both engineers and non-ML stakeholders.
Experience with auto-research, data science agents or agents that write and run experiments.
Experience with tabular, time-series, sensor, test or simulation data.
Previous experience as a backend or platform engineer before moving into AI engineering.
Familiarity with experiment tracking tools and notebook environments.
Experience serving open-source models on GPU infrastructure.
Experience with workflow orchestration for long-running agent tasks.
Experience with fine-tuning or reinforcement learning to improve agent behaviour.
Must be a U.S. person (U.S. citizen or national, U.S. lawful permanent resident, refugee, or asylee) or eligible to access export controlled information without authorization, or eligible and likely to obtain required authorization.

Skills

Python
LLM APIs
Agent frameworks
Tool design
API design
MCP
LLM evaluation
ML fundamentals
Scikit-learn
PyTorch
Retrieval
Context engineering
Code review
Automated testing
CI/CD
Observability
Docker
Kubernetes
AWS
Sandboxing
Authentication
Authorization
Prompt injection
Data isolation
Technical communication

Location

Remote

Work Type

Full-time

Experience Level

Senior
5+ years of professional software engineering experience
2+ years building production systems on top of LLMs

Benefits

Family-level Medical Insurance
Family-level Dental Insurance
Generous Pension Contribution
Life Assurance at 4x Salary
Critical Illness Cover
Employee Assistance Programme
Tuition Reimbursement
Work culture focused on innovative disruption

About the Company

CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence.
Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability.
Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025.
We're proud to be a Living Wage accredited Employer.
We support and encourage an entrepreneurial outlook and independent thinking.
We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems.
As we get set for takeoff, the organization's growth opportunities are constantly expanding.
You will be surrounded by some of the best talent in the industry, who will want to learn from you, too.

Equal Opportunity

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace.
All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.