Head of Solutions Architecture

At ClearML, our mission is to make AI infrastructure effortless across every phase of the AI lifecycle- from building and training models to large scale production. Trusted by more than 2,100 organizations worldwide, AI builders and IT teams use our platform to power everything from early-stage R&D to enterprise-grade AI pipelines.

We’re growing quickly and looking for curious, driven individuals who are excited to shape the future of AI and the infrastructure that powers it. Our customers tackle some of the world’s most important challenges - revolutionizing healthcare, discovering new medicines, securing global finance, protecting national security, and preserving our planet’s ecosystems.

About the Role

We are seeking a Head of Solutions Architecture to lead and scale ClearML’s customer-facing Solutions Architecture organization. This is a hands-on role, including direct technical engagement with customers and combining with team leadership and cross-company alignment.

As Head of Solutions Architecture, you will manage a team of Solutions Architects and work closely with Sales Engineers, Account Executives, Product, R&D, and Customer Success to ensure a consistent, high-quality technical experience across the entire customer journey. The Solutions Architecture team is the technical owner of ClearML’s pre-sales motion, leading customer engagements from initial architecture discussions through successful proof of concept.

You must be adept at explaining complex technical subjects, guiding customers toward clear outcomes, and balancing deep technical problem-solving with operational ownership of the POC pipeline. You should be as comfortable working hands-on in customer environments as you are managing multiple POCs in flight and ensuring they progress efficiently toward success.

This role reports to ClearML’s Chief Revenue Officer.

Requirements:
• Proven experience leading a customer-facing technical team
• At least 2+ years managing solution architects or sales engineers.
• Hands-on experience with Kubernetes-based environments, with a background as a software, DevOps, or platform engineer.
• Strong background in solution architecture, platform engineering, DevOps, or MLOps, with the ability to go deep when needed.
• Comfortable operating both as a hands-on technical contributor and as a leader responsible for the quality and outcomes of others’ work.
• Demonstrated ability to own and drive complex enterprise pre-sales engagements from initial technical discussions through successful POC completion.
• Excellent ability to explain complex technical concepts clearly, guide customers toward defined outcomes, and build trust with technical stakeholders.
• High-ownership mindset, with the ability to set standards, make tradeoffs, and hold teams accountable.
• Comfortable working across time zones in a global, customer-facing role.
• Fluent in English, written and spoken.

Preferred Qualifications

• Experience with AI/ML infrastructure, MLOps platforms, or data engineering.
• Familiarity with Slurm
• Strong architectural understanding of compute, storage, and networking in enterprise environments

Benefits:
Why Join ClearML?

ClearML is on a mission to make AI infrastructure effortless — from early experimentation to large-scale, production-grade systems. Trusted by 2,100+ organizations worldwide, our platform powers real-world, mission-critical AI workloads.

• 🌍 Fully Remote & Global – Work from anywhere with a distributed team of top-tier engineers.
• 🛠 Engineering-First & Autonomous – High ownership, real responsibility, and freedom to design and ship impactful solutions.
• 🚀 High Growth, High Impact – Your work directly affects thousands of users, from startups to large enterprises.
• ⚡ Technically Deep Challenges – Build complex, performance-critical systems at the core of modern AI infrastructure.
• 🔁 Fast Feedback, Real Users – See your work in production quickly and make a measurable difference.

We’re a remote-first team hiring across Europe/ US, with most of the team working within GMT ±3 hours.