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Viral Nation

Solutions Architect, AI Systems

Posted 22 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in Canada
130K-150K Annually
Senior level
Remote
Hiring Remotely in Canada
130K-150K Annually
Senior level
Design, build, and ship end-to-end AI and data solutions using proprietary data infrastructure. Scope projects with business stakeholders, implement models, pipelines, and APIs (Python/SQL), deploy on Snowflake or BigQuery, and iterate post-launch. Enable non-technical teams, collaborate with Data Engineering and AI teams, and operationalize LLMs, embeddings, and predictive models into working internal products.
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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.
  • 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.
This role has an annual salary range of $130,000 to $150,000
 
This range reflects the full scope and progression of the role, from building capability to operating with sustained impact at a higher level. In addition to base salary, we offer a comprehensive benefits and total rewards package designed to support our team as they grow with us.

Where an offer falls within this range is determined through the interview process. Candidates are benchmarked by the hiring team based on role scope, relevant experience, skill alignment, and expected impact, using consistent and objective criteria.
 
Compensation Philosophy:

At Viral Nation, compensation is structured, performance-led, and market-aligned. Pay decisions are intentional, based on role requirements, performance, and market alignment by country, and are set to maintain internal pay equity across comparable roles and levels.

Compensation progression is tied to demonstrated performance, expanded scope, and sustained contribution over time, not tenure alone. Employee compensation is reviewed regularly through formal performance reviews and check-ins to ensure alignment with role expectations and impact.
 
AI in Recruitment:
 
Viral Nation does not use AI-enabled tools to screen, assess, rank, or select candidates – our hiring teams make all hiring decisions. AI note-taking tools may be used during interviews.

DEI Commitment:

Viral Nation is committed to diversity, equity and inclusion in our agency. Viral Nation welcomes applications from people with visible and non-visible disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruiting and selection process.

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