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 .
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Apply Now
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