[Hiring] Solutions Architect @HumanSignal

Role Description

We're looking for a Solutions Architect to join our growing revenue organization. In this role, you'll own the technical relationship across the entire customer lifecycle, pre-sale through post-sale.

• Partner with Account Executives on strategic deals, leading technical discovery, tailored demos, architecture reviews, and proof-of-concepts that prove out Label Studio Enterprise against real customer data and workflows.
• Drive technical onboarding, guiding customers through installation, secure configuration, and best-practice deployment across cloud, on-prem, or hybrid environments.
• Architect integrations between Label Studio and customer AI/ML workflows, pipelines, storage, and enterprise systems.
• Build custom solutions (scripts, plug-ins, and APIs) to extend Label Studio for unique customer requirements.
• Serve as the senior technical escalation point for your accounts, resolving advanced issues and collaborating with Product, Engineering, and Support.
• Deliver enablement, workshops, and documentation that make customer teams self-sufficient on the platform.
• Act as a trusted technical advisor to customer engineering, data, and AI/ML teams, supporting adoption, expansion, and long-term value.

Qualifications

• 5+ years in a customer-facing technical role (Solutions Architect, Sales Engineer, Professional Services Engineer, or similar) for a highly technical product, ideally enterprise SaaS or ML/AI platforms.
• Experience on both sides of the sale is ideal.
• You've built a data labeling pipeline yourself, whether that's data annotation, labeling workflows, or the broader ML lifecycle.
• Hands-on work integrating SaaS platforms with ML pipelines.
• Fluency in Python, REST APIs, and infrastructure tools (Linux/Unix, Docker; Kubernetes a plus).
• A track record of running technical discovery, demos, and proof-of-concepts during the sales cycle.
• Enough business sense to go with the technical depth.
• Executive presence and sharp writing, with the range to move between Data Scientists, ML Engineers, and technical executives.
• Comfortable juggling multiple complex accounts and competing priorities.

Requirements

• You've deployed models to production, or done the engineering to get datasets ready for data science teams.
• You've built against multiple client APIs and SDKs.
• JavaScript, CSS, and HTML are a plus.

Benefits

• Base Salary targeted between $122,500 - 143,500 USD (based on experience and skills).
• Variable compensation; anticipated On-Target Earnings if an employee is meeting objectives are $175,000 - $205,000 USD.
• Stock options.
• Comprehensive health benefits.
• Strong team culture rooted in transparency and collaboration.