AI Solutions Architect

SearchLabs; Toronto; On-site; CAD 120,000 - 200,000; Full time

Job summary

SearchLabs in Toronto is seeking an AI Solutions Architect to lead production-grade GenAI systems, bridging AI architecture, data, cloud, and business needs. You will architect, integrate, deploy, and scale AI solutions beyond POC for real production use.

You will design end-to-end GenAI and LLM-powered architectures, collaborate across teams, and own decisions on latency, cost, and reliability to drive enterprise AI.

Qualifications

• Experience delivering LLM/GenAI systems into production.
• Strong knowledge of RAG, embeddings, vector search, agents, orchestration.
• Experience with cloud providers (AWS/Azure/GCP) and APIs.
• Translate business requirements into scalable AI architecture.

Responsibilities

• 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.
• Collaborate with engineering, data, cloud, product, and business teams to productionize AI use cases.

Skills

GenAI production

LLM systems

RAG pipelines

Vector search

Model orchestration

Embeddings

Cloud platforms

APIs

Data architecture

Distributed systems

MLOps/LLMOps

Observability

Security governance

Guardrails

Job description

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.