Solutions Architect

At Viral Nation, we specialize in building social-first ecosystems for brands to connect with the modern consumer journey. Our integrated solutions align strategy, talent, media, and technology with culturally relevant creativity to scale the world’s fastest-growing digital brands. Viral Nation offers a fluid, creative, and growth-oriented environment that will support your ambitions to apply your talents in an open, collaborative, and fast-paced culture. Our ability to stay at the forefront of the industry has fuelled our success and will guide us in paving the path forward. We’re driven to push boundaries and think beyond today to deliver strategies, and we’re just getting started.

While we continuously exceed our goals, we need your help – our success is only as great as our people. Strong performance leads to high expectations, and we must keep raising the bar!

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.