Director- Site Reliability Engineering

Vendasta•Corman Park No. 344, SK

1d•Hybrid

About The Position

At Vendasta, we’re leading the AI revolution from right here in Saskatoon—and beyond. We work together to empower our partners and customers through our AI-powered customer acquisition and engagement platform to help them get more customers—and keep them. We’re proud to share that Vendasta has officially been named one of Canada’s Most Admired Corporate Cultures for 2025! We’re looking for a Director of SRE who is energized by owning and being accountable for the unit economics of running our platform, treating cost as a first-class reliability concern, and excited to contribute to AI-powered features that enhance our platform. In this role, you’ll play a key part in helping small and medium-sized businesses succeed—while shaping the future of AI for local economies.

Requirements

5+ years in SRE, platform engineering, infrastructure, or DevOps roles operating production SaaS systems at meaningful scale.
Deep hands-on experience with at least one major cloud provider (GCP preferred, AWS or Azure acceptable), including its billing, quotas, and cost management tooling.
Demonstrable track record of taking cost out of a production system, with specific numbers outlining savings driven, trade-offs made, and lessons learned.
Strong fluency in observability and monitoring stacks (Datadog, Prometheus, Grafana, OpenTelemetry) and a clear point of view on where each is worth what it costs.
Comfort writing code to automate cost analysis and enforcement (Python, Go, or similar).
Solid SQL skills for cutting cost data against business dimensions.
A FinOps mindset: treating cost as an engineering discipline, not a quarterly cleanup exercise.
Ability to communicate clearly and effectively in written and verbal formats.

Nice To Haves

FinOps Foundation certification or equivalent experience
Experience operating LLM and AI inference workloads in production, including model routing, prompt caching, and provider arbitrage
Experience evaluating, migrating off, or self-hosting major SaaS infrastructure tools
Familiarity with media transcoding pipelines and CDN economics
Experience working alongside Finance on SaaS metrics such as gross margin, cost of revenue, and unit economics

Responsibilities

Build and maintain dashboards that track daily, weekly, and monthly spend across every system required to run our products: cloud compute and storage (GCP, AWS), observability (Datadog), CDN and media transcoding, LLM and inference providers, third-party APIs, data warehousing, and SaaS infrastructure tools.
Establish baseline cost-per-unit metrics (cost per partner, per SMB account, per AI agent run, per API call) and alert on deviations before they become surprises in the monthly close.
Investigate anomalies the same day they surface, own the root cause analysis, and write up findings the finance and engineering leadership team can act on.
Implement hard and soft spending limits across every cost center: budget alerts, quota caps, rate limits, and circuit breakers on expensive operations (model calls, transcoding jobs, data egress).
Design and roll out cost-aware deployment gates so a team cannot ship a change that 10x’s a line item without explicit review.
Maintain a runbook of “kill switches” for runaway scenarios, tested quarterly.
Continuously evaluate the build-vs-buy posture for every meaningful line item and lead investigations into replacing high-cost vendors with open-source or self-hosted alternatives.
Identify business and product changes that reduce cost of revenue: tier-based feature gating, model routing, caching layers, data lifecycle policies, reserved capacity, committed-use discounts, and contract renegotiation.
Build the business case for each initiative: projected savings, implementation effort, risk, and payback period, driving the work through to measurable savings.
Partner with Finance on monthly close, gross margin reporting, and forecasting to make sure engineering decisions are visible in the financial model.
Work directly with product and platform engineering teams to embed cost-awareness into design reviews, architecture decisions, and on-call practices.
Report regularly to the CEO and leadership team on cost-of-revenue trends, risks, and the savings pipeline.
Complete an inventory of cost of revenue line items, identify owners, set daily dashboards live, and size the top three cost-reduction opportunities within the first 90 days.
Deploy hard limits and alerts across every material spend category, ensure no surprise overruns in the monthly close, and ship at least one major reduction initiative within the first 6 months.
Drive measurable, sustained improvement in gross margin attributable to your work, maintaining a documented and prioritized savings pipeline.