Solutions Architect, AI Systems

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.

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.