Senior Software Engineer, Production Engineering (Cloud & On-Prem) - W&B

Weights & Biases•Sunnyvale, CA

2d•$139,000 - $185,000•Hybrid

About The Position

CoreWeave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME100 most influential companies of 2024. By bringing together CoreWeave’s industry-leading cloud infrastructure with the best-in-class tools AI practitioners know and love from Weights & Biases, we’re setting a new standard for how AI is built, trained, and scaled. The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high-performance training clusters, agent building, and inference at scale, we’re combining forces to serve the full AI lifecycle — all in one seamless platform. Weights & Biases has long been trusted by over 1,500 organizations — including AstraZeneca, Canva, Cohere, OpenAI, Meta, Snowflake, Square,Toyota, and Wayve — to build better models, AI agents and applications. Now, as part of CoreWeave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises. As we unite under one vision, we’re looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you're passionate about solving complex problems at the intersection of software, hardware, and AI, there's never been a more exciting time to join our team. The Production Engineering team builds and operates the platform that lets CoreWeave's engineers ship software quickly, reliably, and safely. We own the observability systems, reliability tooling, incident management systems, and the infrastructure-as-code that underpins our engineering organization's ability to deliver software to our enterprise customers across GCP, AWS, Azure, and self-hosted, on-premises environments. Our mission is simple: you build it, you deploy it, you run it – and we build the tools and processes that make owning your service in production straightforward and safe. We are seeking a Senior Production Engineer with deep expertise across both cloud and on-premises environments to design, build, and operate the reliability platform at the core of CoreWeave's engineering organization. This is a hands-on DevOps/SRE-flavored role: you'll work across infrastructure-as-code, CI/CD, observability, and incident systems – automating away toil and giving service teams the visibility and guardrails they need to run their own code in production. You'll evolve our systems to meet increasingly challenging scale, reliability, and performance demands, and own large, ambiguous operational problems end to end – from error attribution and alert routing to release safety and capacity planning. You'll also provide technical leadership across the team, partnering with senior and principal engineers to influence direction and drive outcomes for cross-functional stakeholders. We care deeply about a sustainable on-call culture, so you'll participate in on-call rotations while championing the architecture and automation that reduce on-call burden over time.

Requirements

Extensive engineering experience designing, building, deploying, and operating critical production infrastructure and services across a large enterprise.
Expert in one or more major public clouds (AWS, GCP, or Azure), with real experience operating on-premises or hybrid environments, and in multi-cloud environments with multi-account strategies
Strong skills in infrastructure-as-code, automation, and configuration management (Terraform, CloudFormation, CDK, Ansible, or similar).
Hands-on expertise with Kubernetes and containerized workloads in production.
Proficient in a systems/scripting language (Go, Python, Bash, or similar) and comfortable writing tooling and automation, not just operating it.
Deep experience with CI/CD (GitHub Actions) and observability / monitoring tooling (Prometheus, Grafana, Datadog, etc.).
Proven ability to evolve designs to meet increasingly challenging scale, reliability, and performance requirements.
Comfortable owning on-call for services you build, and passionate about reducing on-call burden through architecture and automation rather than heroics.
Proven ability to provide technical leadership, work effectively with senior and principal engineers, influence technical direction, and contribute to the success of cross-functional stakeholders.

Nice To Haves

Experience building and operating SaaS products.
Experience building and operating reliability, incident, or developer-productivity platforms (service catalogs / Backstage, PagerDuty tooling, SLO frameworks).
Experience operating stateful systems and databases in production (PostgreSQL, MySQL, ClickHouse, etc.).
Cloud certifications (AWS Solutions Architect, Azure Architect, etc.).
Familiarity with security and access-management best practices in hybrid environments.

Responsibilities

Design, build, deploy, and operate critical reliability and infrastructure services across AWS, GCP, Azure, and on-premises / hybrid environments.
Improve error attribution and alert routing, automatically routing errors and pages to the team that owns the affected service, so engineers are only on-call for what they own.
Own observability patterns, SLI/SLO frameworks, service catalog metadata, and dashboards that give teams visibility into their services from code change through production.
Build release-safety systems – canary deployments, smoke tests, staged rollouts, and reliable roll-back / roll-forward – so shipping to production is fast and safe.
Advance the incident and on-call program – incident tooling, on-call rotations, runbooks, and operational readiness reviews; measure incident volume by team to focus reliability investment.
Reduce on-call burden through better architecture, automation, and observability – and participate in on-call rotations yourself.
Provision and manage infrastructure with Terraform and drive manual, incident-time operations toward automated, repeatable infrastructure-as-code.
Break down and solve large, ambiguous operational problems, turning them into well-scoped, shippable engineering work.
Provide technical leadership and mentorship, work alongside senior and principal engineers, and influence the broader technical direction of the platform.