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. Learn more at www.coreweave.com.

What You’ll Do

The Global Field Organization (GFO) at CoreWeave makes sure every client running AI workloads at scale has a seamless, reliable, and high-performance experience. Within the GFO, the SaaS Technical Support Engineering team supports CoreWeave Forge, the platform ML engineers and researchers use to track experiments, manage models, and build with LLMs. The team works directly with customers to debug training workflows, resolve SDK and API integration issues, and keep their AI development moving. The GFO team works closely with internal and customer engineering teams, so the SaaS TSE team brings insight from the field back to Forge product and engineering and helps shape the CoreWeave product roadmap.

About the role

Respond to inbound support requests across email, Slack, and community forums, triaging by customer tier and severity and meeting response SLAs
Own technical escalations end-to-end: investigate using logs, traces, and dashboards (we use Datadog and Grafana), reproduce issues, and write clear, structured escalations that engineering can act on
Debug issues across the full breadth of our growing Forge product suite — from experiment tracking to agentic AI tooling — across every deployment model, from our cloud to customers' own environments
Coordinate across engineering, product and other internal teams to drive customer issues to resolution — and keep customers informed with a kind, thoughtful tone throughout
Recognize incidents, engage on-call engineering through our incident process, and communicate status to affected customers
Be the voice of the customer — advocate for product improvements on their behalf, and spot trends in user messages to improve internal and external documentation
Deliver clean written handoffs as part of a follow-the-sun support model spanning APAC, North America, and EMEA, with participation in a weekend and holiday on-call rotation
Mentor teammates on troubleshooting approach and escalation quality, and encourage team building through knowledge sharing and a collaborative, supportive team culture

Who You Are

2+ Programming experience, from either an engineering role, a computer science degree, or personal projects
Python proficiency
Experience with logging and monitoring tools such as Datadog
Familiarity with Single Sign-On (SSO) concepts and API integration/knowledge
Experience using developer and AI-assisted tooling such as Claude Code, Codex, and modern debugging tools
A passion for connecting with real users and enabling them to be power users of the product
Good organization of assigned requests to oversee timely follow-up for every message
Work autonomously in a self-directed environment
Proactively find ways to improve processes and collaborate internally
Answer messages with a kind, thoughtful tone that makes users feel appreciated and connected to our team

Preferred

Customer service experience in a technical SaaS environment
Previous experience in AI development
Experience in frontend frameworks
Experience with Docker, AWS, GCP, Azure
Experience with Kubernetes or other cloud infrastructures

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.

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.