Forward Deployed Engineer, AI Agents

About the role

CoreWeave seeks a Forward Deployed Engineer to operate directly within customer AI teams, enabling them to design, iterate, and productionize sophisticated AI agents using the W&B Weave developer toolkit. This position demands a hands-on engineer who thrives at the intersection of product, infrastructure, and customer outcomes, solving ambiguous challenges that have no single prescribed path. You will act as a critical bridge between customer workflows and CoreWeave's platform capabilities, translating real-world agentic workloads into robust reference implementations. The role involves deep collaboration with product, engineering, and customer teams to validate architecture, surface constraints, and accelerate time-to-value for AI initiatives. You will be responsible for shaping the narrative of how AI agents are built, deployed, and scaled in production environments by providing expert guidance at the earliest stages of exploration. Success in this position is measured by your ability to de-risk customer deployments, drive adoption of best practices, and ensure that agentic systems perform reliably at scale. This is an opportunity to influence the future of AI infrastructure tooling while working alongside some of the most innovative organizations building with artificial intelligence.

Key facts

What you'll do

• Embed within customer AI engineering teams to architect, prototype, and deploy production-grade AI agents leveraging the W&B Weave platform.
• Serve as a trusted technical advisor, guiding customers through architectural decision frameworks and established best practices for agentic workflow design.
• Create and maintain reference implementations, end-to-end demos, and example projects that illustrate effective patterns for building with W&B Weave.
• Collect, analyze, and synthesize qualitative and quantitative feedback from deployed agents to inform the W&B Weave product roadmap and enhance the developer experience.
• Lead technical workshops, deep-dive sessions, and enablement clinics aimed at accelerating customer adoption and proficiency with agentic tooling.
• Diagnose, isolate, and resolve complex technical issues that arise in customer environments, ensuring continuity and reliability of agent deployments.
• Collaborate with product managers and engineers to translate customer use cases into coherent feature requests and platform improvements.
• Evaluate emerging agentic frameworks and orchestration strategies, determining fit for integration within customer workflows on W&B Weave.
• Document technical workflows, patterns, and configurations to build a reusable knowledge base for both customers and internal teams.
• Partner with sales and solutions engineering teams to develop technical narratives that communicate value and differentiate CoreWeave's platform.
• Support proof-of-concept initiatives from initial scoping through successful production deployment, providing technical leadership throughout the lifecycle.
• Continuously refine your expertise in large language models, reinforcement learning, and vector search to address evolving customer requirements.

Requirements

• Strong engineering background with demonstrable experience in Python and modern ML/AI systems frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, and LlamaIndex.
• A minimum of a bachelor's degree (or international equivalent) in Computer Science or a closely related quantitative field is required.
• Hands-on experience developing, training, or deploying language models and AI agents using contemporary orchestration frameworks.
• Prior work in roles involving direct customer interaction, technical consulting, or solutions engineering within fast-paced technology environments.
• Exceptional verbal and written communication skills, with the ability to distill intricate technical subjects for both technical and executive stakeholders.
• Demonstrated comfort operating in ambiguous, rapidly shifting environments where creative problem-solving and adaptability are essential.
• A proven track record of ownership, reliability, and follow-through in delivering technical outcomes under tight deadlines and shifting priorities.
• Proficiency with version control, debugging, and profiling tools relevant to ML workloads and distributed systems.
• Understanding of cloud infrastructure patterns, networking fundamentals, and deployment pipelines in multi-tenant environments.
• Willingness to engage with customers at all levels, from individual contributors to technical leadership, to ensure alignment and shared understanding.
• Commitment to maintaining a high standard of technical excellence, security, and compliance in all customer-facing deliverables.
• Ability to travel as needed for customer engagements, including occasional extended stays and participation in on-site reviews.

Nice to have

• Experience building production ML/AI systems at scale, including data pipelines, model serving, and monitoring infrastructure.
• Deep familiarity with vector databases, retrieval-augmented generation techniques, and reinforcement learning frameworks.
• Prior forward deployed, field engineering, or solutions architect roles in AI, cloud infrastructure, or enterprise software.
• Contributions to open source projects related to machine learning, agent frameworks, or developer tooling.
• Experience with observability, logging, and tracing for AI workloads in distributed environments.
• Knowledge of regulatory and compliance considerations around AI deployment in enterprise contexts.

Practical notes

• Hours: Full-time.
• Travel: Required for customer engagements, including occasional extended stays and on-site reviews.
• Visa: Sponsorship may be available for qualified candidates.
• Deadlines: Applications should be submitted as soon as possible for consideration.