Sobre este puesto de Solutions Architect en HumanSignal
About HumanSignal
Real-world data is the competitive edge in AI.
HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.
We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.
We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.
If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.
About the Opportunity:
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.
You'll be the technical partner behind our most strategic enterprise accounts, from first conversations through production scale. Working alongside Account Executives, you'll lead technical discovery, demos, and proof-of-concepts, then carry that same solution through onboarding, workflow design, integration, and ongoing optimization. You'll be your customers' trusted technical advisor at every stage of their Label Studio Enterprise journey.
Label Studio is a deeply technical product, used by Data Scientists and ML Engineers as core infrastructure for their work. To succeed here, you'll need a real understanding of data labeling and the role it plays in model performance. You'll work directly with ML Engineers, Data Scientists, and MLOps teams to architect solutions that hold up in production.
What You’ll Do:
- 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.
What You'll Bring:
- 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. You can explain how it works to an engineer and to a VP without changing much.
- Hands-on work integrating SaaS platforms with ML pipelines. You've deployed models to production, or done the engineering to get datasets ready for data science teams.
- Fluency in Python, REST APIs, and infrastructure tools (Linux/Unix, Docker; Kubernetes a plus). You've built against multiple client APIs and SDKs. JavaScript, CSS, and HTML are a plus.
- A track record of running technical discovery, demos, and proof-of-concepts during the sales cycle, then owning onboarding, implementation, troubleshooting, and custom development after the close.
- Enough business sense to go with the technical depth. You can take a customer's problem and hand it back to them as a value proposition they actually recognize, and you can see an objection coming before it lands.
- 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.
We are hiring for this role across North America. Base Salary is targeted between $122,500 - 143,500 USD (based on experience and skills). This role also qualifies for variable compensation; anticipated On-Target Earnings if an employee is meeting objectives are $175,000 - $205,000 USD. This range is provided by market data and is in good faith. Final offer details are determined by several factors including candidate experience, expertise as well as applicable industry knowledge, and may vary from the pay ranges listed above. We also offer stock options, comprehensive health benefits, and a strong team culture rooted in transparency and collaboration. Join us!
