Senior Solutions Architect

Core Weave is The Essential Cloud for AI™. Built for pioneers by pioneers, Core Weave 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, Core Weave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, Core Weave became a publicly traded company (Nasdaq: CRWV) in March 2025.

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Our Solutions Architecture team at Weights & Biases is a unique hybrid organization, combining the deep technical skills of Site Reliability Engineering with the consultative expertise of Solutions Architecture. We focus on ensuring customers can successfully deploy and operate W&B across cloud and on‑prem environments while delivering a best‑in‑class experience that accelerates ML adoption at scale.

As a Solutions Architect, you will be responsible for managing complex customer deployments across AWS, GCP, Azure, and on‑prem environments. You’ll partner directly with customer engineering teams to provision and monitor services, debug and resolve infrastructure issues, and ensure performance and scalability using SRE best practices. This role blends hands‑on technical problem‑solving with customer‑facing engagement, including technical discussions, demos, workshops, and enablement content creation.

You’ll work closely with Sales Engineering, Field Engineering, Support, and Product to drive adoption and influence our product roadmap based on customer feedback.

• Proven track record of systematically diagnosing and resolving infrastructure issues
• Experience in a customer‑facing technical role
• Expertise in Docker, Kubernetes, Helm charts, networking, and cloud‑managed services (e.g., MySQL, Object Stores)
• Strong fundamentals in Infrastructure as Code (IaC), preferably Terraform
• Proficiency with at least one cloud platform (AWS, GCP, Azure); experience across multiple platforms is a plus
• Strong Linux/Unix command line experience
• Basic proficiency in Python and familiarity with ML workflows or tools

• Deep proficiency in Kubernetes design patterns, including Operators
• Familiarity with data engineering and MLOps tooling
• Experience as an educator or facilitator for technical training sessions, workshops, or demos
• SaaS, web service, or distributed systems operations experience

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. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love diving into infrastructure problems and solving them systematically
• You're curious about how to scale complex ML systems in production environments
• You're an expert in building and running containerized, distributed systems

We work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for takeoff, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too.

Come join us!

The base salary ranges for this role is $180,000 to $200,000. The starting salary will be determined based on job‑related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base…