Senior AI Engineer

Ovii's Interpretation of the Role

Senior AI Engineer building end‑to‑end AI‑powered features and integrating them into production‑grade backend platforms. Works cross‑functionally with product, architecture, and data teams while mentoring engineers. Hybrid role based in Toronto.

Role Snapshot

• Senior AI Engineer
• Hybrid (Toronto)
• Full‑Time
• AI/ML feature development
• Backend platform integration
• Mentor engineers

Must-Have Requirements

• Python
• ML frameworks (TensorFlow, PyTorch, Scikit‑learn)
• Backend API development (Node.js/TypeScript)
• SQL
• Cloud platforms (GCP or AWS)
• scalable production‑grade software
• hands‑on AI/ML model deployment
• Bachelor's degree in Computer Science, Data Science, AI, or related field

Nice-to-Have Signals

• Data platforms & analytics
• Real‑time processing (Kafka, SQS)
• Fintech or compliance domain experience
• Multi‑tenant SaaS platform design
• ERP integration experience
• Familiarity with MLOps best practices
• data platforms & analytics
• real‑time processing
• fintech or compliance domain

Work Setup

• Location: Toronto, Canada
• Work mode: HYBRID
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Relocation
• Travel requirement
• Security clearance
• Coding test

What You'll Likely Work On

• Design, implement, and ship AI‑powered features from model integration to production monitoring
• Integrate LLM APIs and ML models into scalable backend services
• Fine‑tune models for performance, reliability, and cost efficiency in live environments
• Build robust APIs, event‑driven services, and third‑party integrations that enable AI workflows
• Create and maintain data pipelines and MLOps workflows for model lifecycle management
• Contribute to system architecture decisions and reusable AI framework design
• Lead code reviews, enforce quality standards, and mentor engineers across teams
• Troubleshoot complex production issues in distributed, AI‑integrated systems

Good Fit If You Have

• Experience with data platforms, analytics, or ETL pipelines
• Familiarity with real‑time processing tools such as Kafka or SQS
• Background in fintech, compliance, or enterprise SaaS product development