AI Solution Architect
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
Job Description
- Own the full AI lifecycle - from data ingestion and preparation through model training, evaluation, and production deployment.
- Engineer data pipelines, APIs, and orchestration layers to integrate AI solutions with enterprise systems.
- Ensure solutions are secure, scalable, and compliant with client IT and governance policies.
- Build automated evaluation loops for model quality, bias detection, and performance monitoring.
- Quantify ROI and business value post-deployment and feed learnings back into reusable frameworks and blueprints.
- Embed transparency, explain ability, audit trails, and data-lineage tracking in every solution.
- Partner with client risk and compliance teams to ensure adherence to Responsible AI principles.
More about this job
Responsibilities
Own the AI lifecycle from data preparation and model development through evaluation and production deployment, while engineering pipelines, APIs, and orchestration layers for enterprise integration. Monitor quality, bias, performance, ROI, transparency, and data lineage, and work with client risk and compliance teams to ensure responsible and policy-compliant solutions.
Requirements
The role calls for mid-senior-level capability in designing and delivering end-to-end AI solutions, including data pipelines, model evaluation, and production deployment. It also requires attention to security, scalability, governance, Responsible AI, auditability, and business value measurement.
Skills
- AI Lifecycle Management
- Data Ingestion
- Data Preparation
- Model Training
- Model Evaluation
- Production Deployment
- Data Pipeline Engineering
- API Integration
- Orchestration
- Security
- Scalability
- Governance Compliance
- Bias Detection
- Performance Monitoring
- Responsible AI
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Consulting
- Engineering
Keywords
- AI Lifecycle
- Data Ingestion
- Data Preparation
- Model Training
- Model Evaluation
- Production Deployment
- Data Pipelines
- APIs
- Orchestration Layers
- Enterprise Systems
- Security
- Scalability
- IT Governance
- Automated Evaluation Loops
- Model Quality
- Bias Detection
- Performance Monitoring
- ROI
- Business Value
- Reusable Frameworks
- Blueprints
- Transparency
- Explainability
- Audit Trails
- Data Lineage
- Risk Management
- Compliance
- Responsible AI