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 the design, development, and delivery of scalable generative AI products and enterprise solutions, including LLM pipelines, agentic workflows, and Graph/RAG applications on AWS. Collaborate with product and data teams, provide technical leadership, manage delivery milestones, and improve production reliability, performance, and governance.

Job details

Role: Sr AI Engineer Location: Toronto, ON Duration: Long Term Contract Job Description: • AI Product Delivery: Lead and actively contribute to the development of AI products, pilots, and enterprise solutions with a focus on writing clean, maintainable code. • Architecture & Design: Design and architect scalable Generative AI solutions, including LLM pipelines, Agentic workflows, Model Context Protocol (MCP), Graph/RAG architectures, and complex prompt-based applications. • Cloud Infrastructure: Implement highly scalable, cloud-native solutions leveraging modern AWS services. • Optimization & Innovation: Optimize the performance of production AI products. Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and emerging toolchains. • Cross-Functional Collaboration: Partner closely with Product Managers, Data Scientists, and domain experts to translate business requirements into robust technical solutions. • Technical Leadership: Act as an organization-wide Subject Matter Expert (SME) on Gen AI technologies to help shape the company's long-term AI strategy and technical roadmap. • Project Ownership: Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban) to ensure reliable end-to-end product delivery. • Operations & Governance: Monitor operational metrics and incident data to improve system reliability. Ensure strict adherence to corporate governance and DevSecOps protocols. Required Experience & Skills Technical Expertise • 10 + years of progressive engineering experience. - DO NOT SUBMIT LESS THEN 10 YRS EXP. • 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 at least 10 years of progressive engineering experience and 1–2 years leading emerging technology or enterprise AI initiatives. Candidates should have hands-on expertise in generative AI frameworks and architectures, AWS and DevSecOps, Python and modern web development, databases and orchestration, and AI and web testing tools.