Solutions Architect - Sales, NAM

About Hilbert

Hilbert is a scalable, data science-first growth engine that gives B2C teams predictive clarity into user behavior, revenue drivers, and the actions that drive sustainable growth. Fully agentic by design, Hilbert shrinks months-long decision cycles to minutes. From Fortune 10 enterprises to beloved brands like FreshDirect, Blank Street, and Levain Bakery, operators run their growth on Hilbert. 

The Mission: Win the Technical Evaluation

Hilbert is hiring a Solutions Architect to lead the technical side of enterprise deals. You support several account executives, carry several accounts at once, and position Hilbert as the growth layer on top of the customer's existing data stack. As the first Solutions Architect in your region, you set how the function works. 

You run the technical evaluation with the prospect's data, engineering and security teams, map how Hilbert connects to their data and advertising platforms, present the deployment patterns our product engineering team has designed, propose the one that fits, and write the solution design and feasibility assessment the proposal is built on. 

What you'll do 

• Own the technical strategy for your accounts from first discovery to a signed scope, ending in a documented solution design. 
• Find the data access path and its owner early, before it stalls the deal. 
• Own the vendor security review with a named counterpart on the customer's security team, covering encryption, anonymization and hashing, role-based access control, retention, model-training boundaries and access revocation. 
• Present Hilbert's deployment and integration patterns and explain how our ML models and agents work, spanning data ingestion, ML scoring and activation into advertising and CRM platforms, and bring modification requests to our product engineering team when a customer's setup needs one.
• Start from the potential customer’s growth goal and translate growth use cases such as reactivation, acquisition quality, cross-sell and product propensity into a data and activation design the prospect's engineers agree is buildable. 

• Win the technical evaluation in competitive deals: GTM lead runs the product demo, and you run the architecture walkthrough, the live technical questions and the proof on the prospect's own data and stack. 
• Turn the proof into a business case in dollars with the GTM lead, and defend it to the client side.
• Hand each signed scope to our delivery engineers. 
• Bring new cases and structured feedback to our engineering and product teams, and keep learning from them as the product grows. 
• You are measured on technical wins, how quickly prospects get a clear feasibility answer, first technical engagement to contract conversion, how efficient the technical part of the sales process gets with your contribution.

What you bring

• Extensive experience in technical pre-sales, solutions architecture, data engineering or consulting, scoping data and ML solutions for enterprise buyers. 
• The perfect mix between technical experience and customer-facing readiness mindset.
• You have carried enterprise security and architecture reviews in a regulated industry to a decision, and you know the difference between a question and a blocker. You read a customer data stack in one call: warehouse (ClickHouse, Databricks, Snowflake, BigQuery, Redshift), CDP, CRM, ad platforms and their APIs, at the level of what goes where and what it costs to move. 
• Fluency in deployment and data-boundary concepts, enough to present them and spot what a customer needs changed: VPC and private link, cross-cloud connectivity, compute in place, data sharing, egress cost, data residency, SOC 2 and ISO 27001 requirements. 
• Hands-on SQL, comfort reading Python, being able to implement scripts when necessary. 
• Clear writing and compelling presentation: solution designs, data flows and interfaces an engineer can build from. You present to a CTO or a CMO as easily as to their engineers, and you say "not feasible" when it is not. 
• Startup pace: several evaluations open at once, with no team to delegate to at first
• Fluency in your region's business language. 

Nice to have 

• A Databricks or Snowflake certification. 
• Growth-focused data projects across industries, regulated or not, such as e-commerce, retail, fintech, telco, or media. 
• Experience at a CDP or ad-tech vendor, or on the customer side of an ML or CDP deployment. 

Reporting and location

You report to the regional GTM leader and work as the technical counterpart to the region's account executives. Our product engineering team designs the deployment patterns you present, you might adjust with slight differences and our engineering delivery team reviews every solution design before it reaches a customer and they deliver it. You are based in the region, close to prospects, with travel of around 50 percent.

Interview process

1. Recruiter screen, 30 minutes.
2. Hiring manager, 45 minutes: a deal you owned from discovery to signed scope.
3. Architecture session with our engineering team, 60 to 90 minutes: an anonymised client stack, which deployment pattern fits, and the security questions it raises.
4. Build and pitch: from a client brief and an anonymised consumer dataset, produce a use case, a proof of concept design and a business case, then present for 20 minutes.
5. References: two from clients, one from a sales colleague.

Why join us

At Hilbert, we move fast, work collaboratively, and give people real ownership over their impact. As a fast-growing company, there's no shortage of room to grow — you'll take on new challenges quickly and shape the path as you go.

Hilbert is an Equal Opportunity Employer. We are committed to building a diverse team and an inclusive culture, and we welcome applicants of all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other status protected by applicable law.