Closed listing
AI Solutions Architect
- Toronto, ON, Canada
$180,000 to $200,000 CAD / year · Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Pay
- $180,000 to $200,000 CAD / year
- Job type
- Full-time
- Closing date
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
Are you an AI Solutions Architect who has actually taken AI into production?
Have you designed systems using LLMs, RAG, agents, vector search, and model orchestration beyond the POC stage?
Do you want to help shape how a growing organization builds and scales production-grade AI?
We’re working with a Toronto-based organization making a significant investment in AI and looking for someone who can bridge AI architecture, engineering, data, cloud, and the business.
This is not simply a Software Engineer using AI tools to code. We’re looking for someone who has been responsible for architecting, integrating, deploying, and scaling AI systems in real production environments.
What You’ll Do
- Architect end-to-end GenAI and LLM-powered solutions from POC through production.
- Design RAG pipelines, agentic workflows, model orchestration, and enterprise AI integrations.
- Build architectures across LLM APIs, embeddings, vector databases, data pipelines, APIs, and cloud infrastructure.
- Define approaches around model evaluation, observability, security, governance, and guardrails.
- Make architectural decisions around latency, scalability, reliability, cost, and model performance.
- Work across engineering, data, cloud, product, and business teams to turn AI use cases into production systems.
You Are
- Experienced delivering LLM / GenAI systems into production, not just prototypes.
- Strong across RAG, embeddings, vector search, agents, prompt/model orchestration, and AI APIs.
- Comfortable with AWS/Azure/GCP, APIs, data architecture, distributed systems, and modern software architecture.
- Familiar with MLOps/LLMOps, evaluation frameworks, monitoring, AI security, and responsible AI practices.
- Able to translate complex business requirements into scalable AI architecture.
Why This Role
- Real AI Engineering – production systems, not AI demos.
- Architecture Ownership – influence how AI is designed, integrated, governed, and scaled.
- Strong Compensation – up to $200K+ base.
- Toronto Hybrid – 2-3 days per week on-site.
More about this job
Responsibilities
Architect and deploy end-to-end GenAI and LLM-powered solutions from POC to production. Design RAG pipelines and agentic workflows while managing model evaluation, observability, and security.
Requirements
Proven experience delivering production-grade LLM systems and expertise in vector databases and cloud infrastructure. Ability to translate complex business requirements into scalable AI architectures.
Skills
- AI Architecture
- LLM
- RAG
- Vector Search
- Model Orchestration
- Agentic Workflows
- AWS
- Azure
- GCP
- MLOps
- LLMOps
- Data Architecture
- Distributed Systems
- AI Security
- Prompt Engineering
- Cloud Infrastructure
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Science & Research
Keywords
- Artificial Intelligence
- Generative AI
- LLM
- RAG
- Vector Databases
- Embeddings
- Model Orchestration
- MLOps
- LLMOps
- AWS
- Azure
- GCP
- Distributed Systems
- AI Governance
- AI Security
- Responsible AI
- API Integration
- Cloud Infrastructure
- Data Pipelines
- Scalability
- Latency Optimization
- Model Evaluation
- Observability
- Guardrails
- Enterprise AI