Sr AI Engineer

Toronto, ON
On-site
Posted Oct 15, 2026
1 position

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Employment type: Contract
Experience level: Lead · 10+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Lead emerging technology or enterprise AI initiatives and develop AI solutions using commercial and open-source language models, agentic AI, and Graph/RAG architectures. Build and support cloud-based, full-stack applications and data workflows, applying SDLC, DevSecOps, testing, and analytics practices.

Job details

Technical Expertise • 10 + years of progressive engineering experience. • 1–2 years of direct experience leading emerging technology or enterprise AI initiatives. • Strong familiarity with the full Software Development Life Cycle (SDLC) best practices and DevSecOps protocols. • Generative AI & LLMs: Core proficiency with commercial and open-source models (GPT, Claude, Gemini, LLaMA), advanced prompt engineering, and LLM fine-tuning techniques. • AI Frameworks & Architectures: Deep hands-on experience with LangChain, LlamaIndex, Amazon Bedrock, Agentic AI, MCP, and Graph/RAG architectures. • Databases & Orchestration: Proven experience with Vector and Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune), query optimization, and ETL orchestration using Apache Airflow/DAGs. • Cloud & DevOps (AWS): Comprehensive knowledge of AWS infrastructure, including computation (EKS, Fargate, Lambda, EC2), networking/load balancing (ELB, GLB, NLB), data analytics (Athena, Glue, Lake Formation), and Infrastructure as Code (Terraform, Puppet, Docker). • Full-Stack Development: Strong proficiency in Python (NumPy, Pandas, Matplotlib, Boto3) alongside modern web application development using Next.js, React, and TypeScript/JavaScript. • Testing & Analytics: Familiarity with automated AI and web testing frameworks (Ragas, Playwright, Zephyr, Selenium) and Business Intelligence tools (QuickSight, Tableau).

What you’ll do

Requirements

Requires 10+ years of progressive engineering experience and 1–2 years leading emerging technology or enterprise AI initiatives. Candidates should have hands-on expertise in LLMs, AI frameworks, databases, AWS, Python, modern web development, orchestration, testing, and business intelligence tools.