As an Embedded AI Engineer, you'll bridge technical and operational needs by building intelligent systems that enhance how teams work. You'll lead the full lifecycle of AI integration—from identifying workflow inefficiencies to launching and scaling solutions that deliver real impact.
What You'll Do
- Guide embedded AI initiatives from initial discovery through deployment and long-term scaling, defining KPIs and ensuring alignment with team goals.
- Develop full-stack internal applications that teams use daily, balancing rapid iteration with sustainable architecture.
- Evolve shared AI platforms used across multiple teams, treating them as strategic assets that compound value over time.
- Clarify ownership models for each solution—whether shared, co-owned, or transitioned to a permanent home team.
- Define success metrics early and refine solutions until measurable outcomes like time savings, error reduction, or throughput gains are achieved.
- Build reusable frameworks, templates, and documentation to accelerate future projects.
- Collaborate across engineering and business functions, clearly communicating scope, tradeoffs, and change management plans.
Requirements
- At least two years of experience delivering production-grade software systems.
- Strong coding skills in backend languages such as Python or Ruby, with the ability to work across frontend (TypeScript/JavaScript/React) and backend environments.
- Demonstrated ability to clarify ambiguous processes and deliver focused MVPs in collaboration with domain experts.
- Hands-on experience applying large language models and AI agents to automate real-world workflows.
- Excellent communication skills, with experience leading technical discussions, demonstrating prototypes, and driving user adoption.
- Deep understanding of AI applications: you restructure workflows using AI, track outcomes, and quantify impact through metrics like error reduction, time saved, and increased velocity.
Preferred Qualifications
- Background in developing internal tools and integrating with platforms like CRM, ticketing systems, knowledge bases, or analytics engines.
- Experience operationalizing AI workflows at scale.
Technical Stack
Ruby, Python, TypeScript, JavaScript, React, LLMs, AI agents
Benefits
- Stock options and retirement planning support with 4% matching (401(k) in the U.S., TFSA/RRSP in Canada)
- Comprehensive medical, dental, and vision coverage for employees and dependents
- Unlimited paid time off (salaried) plus company holidays and designated focus periods
- Generous parental leave: up to 12 weeks paid after six months of service (U.S.), EI top-up available (Canada)
- Life insurance and short- and long-term disability coverage
- Access to paid AI tools with minimal restrictions
- Work From Anywhere Month and meeting-free weeks each year
- Meals, commuter benefits, team offsites, and Customer Days
