We have one of the largest and most advanced proprietary data infrastructures in the world, spanning social, customer, and sourced datasets. The next step is turning that data into scalable, AI-driven products — not just models and dashboards, but working software that ships.

We're seeking a Solutions Architect, AI Systems who owns a problem end to end: scopes it with the business, designs the system, and then builds the first working version themselves. This is a builder's role. You architect the solution and you ship it — the two don't get handed off between different people.

What You'll Do Here:

• Partner with executive, strategy, and client teams to scope AI and data solutions from an ambiguous business problem to a concrete technical plan.
• Design the system, then build and ship the first working version yourself — architecture and delivery sit with the same person.
• Build and deploy functional tools, models, and internal products on our proprietary data infrastructure (Snowflake, BigQuery) — not dashboards alone.
• Write and maintain working code (Python, SQL, APIs) to operationalize models and pipelines — doesn't need to be enterprise-grade, needs to run.
• Deploy applied AI methods — LLMs, embeddings, predictive modeling — as real, working features, not proofs of concept that stall at the deck stage.
• Collaborate with Data Engineering and AI teams to keep infrastructure aligned and data quality high as you build.
• Build internal enablement tools that let non-technical teams use and scale what you've shipped.
• Own your solutions past launch — monitor real usage, iterate, and improve.

You'll Need To Have:

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field — or equivalent experience demonstrating technical excellence and business fluency.
• 5+ years in Solutions Architecture, Applied AI/ML Engineering, or Data Engineering, with a track record of shipped, working software — not just designs, specs, or dashboards.
• Proficient in Python (or a comparable language) and SQL; comfortable writing and deploying code that runs in production, even if it isn't polished.
• Experience building and deploying models, pipelines, or applications on cloud data platforms such as Snowflake or BigQuery.
• Working knowledge of LLMs, embeddings, and applied AI methods, with real experience shipping them into working tools.
• BI tool fluency (Sigma, Tableau, Looker, Power BI) is a plus — not a substitute for engineering ability.
• Product mindset — comfortable owning a problem from an ambiguous ask through to a deployed, working solution.
• Comfortable operating in ambiguous, fast-moving problem spaces without a large team around you.
• Background in marketing, the creator economy, or social intelligence is a strong asset.
• Please include a link to something you've built and shipped — a repo, a deployed app, or a demo — with your application.