Production Engineer, Support tooling (Tooling and Frameworks)

CoreWeave•Livingston, NJ

1d•$139,000 - $204,000•Hybrid

About The Position

The Production Engineering team sits at the heart of CoreWeave’s reliability efforts. In this role, you’ll partner closely with our Support/CX teams to build, operate, and evolve internal tooling that enables a “Direct‑to‑Expert” support model at scale. You’ll define and ship AI‑assisted workflows, self‑service diagnostics, and platform integrations that reduce time‑to‑resolution and improve customer experience across our cloud.

Requirements

4+ years of software or infrastructure engineering experience building and operating production services.
Proficiency in Go or Python (or equivalent experience).
Strong fundamentals in Linux, containers, and Kubernetes; comfortable debugging in distributed systems.
Experience with observability (metrics/logs/traces) and using data to improve reliability and support outcomes.
Demonstrated experience with incident management and steady‑state operational excellence (e.g., progressive delivery, testing strategies, error budgets, fault‑tolerant design).
Comfort collaborating with multiple stakeholders (Support/CX, Product, SRE, and service owners).

Nice To Haves

Experience integrating or building support/operations tooling (e.g., ticketing/incident systems, status page, knowledge management, chat/alerting integrations).
Experience automating manual workflows and stitching together productivity platforms.
Familiarity with AI/ML tooling for retrieval, summarization, or copilot‑style assistance.
Experience codifying operational practices into Kubernetes controllers, operators, or platform services.

Responsibilities

Design, build, and own support-facing tools for case triage, intelligent routing, and expert engagement, integrating with incident and change management workflows.
Develop AI‑powered assistants and automations that accelerate root‑cause discovery, knowledge retrieval, and resolution quality.
Create and maintain dashboards, alerts, and signals that surface tooling issues early; integrate observability into new tooling to reduce MTTR.
Build self-service and guided diagnostics that empower Support/CX to resolve common issues and collect high‑quality context for escalations.
Codify reliability and support practices into services, APIs, and Kubernetes-native controllers/operators where appropriate.
Partner with engineering leadership and internal stakeholders to prioritize roadmap initiatives, land adoption, and measure business impact.
Participate in an on‑call rotation for the tooling you own.