Artificial Intelligence Engineer

Job summary

Lead the design, development, optimization, and delivery of scalable generative AI products and enterprise solutions using LLM pipelines, agentic workflows, and Graph/RAG architectures on AWS. Collaborate across product and technical teams, provide organization-wide AI expertise, manage delivery milestones, and uphold operational reliability, governance, and DevSecOps practices.

Job details

Role: Sr AI Engineer Location: Toronto Downtown, ON - Hybrid (4 Days WFO) Hiring Mode: 6-12 months Contract with possibility of extension Key Responsibilities 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. 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

Lead the design, development, optimization, and delivery of scalable generative AI products and enterprise solutions using LLM pipelines, agentic workflows, and Graph/RAG architectures on AWS. Collaborate across product and technical teams, provide organization-wide AI expertise, manage delivery milestones, and uphold operational reliability, governance, and DevSecOps practices.

Requirements

Requires 10+ years of progressive engineering experience, including 1–2 years leading emerging technology or enterprise AI initiatives, and strong SDLC and DevSecOps knowledge. Candidates should have hands-on expertise in generative AI, AWS, AI frameworks and architectures, vector and graph databases, orchestration, Python, modern web development, and testing and analytics tools.

Listed skills

• prompt engineering · Preferred
• Amazon Web Services · Preferred
• Python · Preferred
• React · Preferred
• Next.js · Preferred
• TypeScript · Preferred
• Terraform · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Generative AI
• Large Language Models
• Prompt Engineering
• LLM Fine-Tuning
• LangChain
• LlamaIndex
• Amazon Bedrock
• Agentic AI
• Model Context Protocol
• Graph/RAG Architectures
• AWS
• Python
• React
• Next.js
• TypeScript
• Terraform

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Management & Leadership

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