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Generative AI Engineer

  • Toronto, ON, Canada

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Original job description

Role : Senior AI Engineer – Generative AI

Location : Toronto ,ON

Experience: 8+ years

Role Summary

  • Lead the development and delivery of enterprise GenAI products, pilots, and scalable AI solutions.
  • Architect LLM pipelines, Agentic AI workflows, MCP, Graph RAG, and prompt-based applications.
  • Build cloud-native AI solutions using AWS and optimize production performance.
  • Collaborate with product, data science, and business teams to deliver AI solutions.
  • Drive technical strategy, Agile delivery, DevSecOps, governance, and production reliability.

Required Skills

  • 10+ years of engineering experience, including 1–2 years leading AI initiatives.
  • GenAI/LLMs: GPT, Claude, Gemini, LLaMA, prompt engineering, fine-tuning.
  • AI Frameworks: LangChain, LlamaIndex, Amazon Bedrock, Agentic AI, MCP, Graph RAG.
  • Databases & Orchestration: Weaviate, Milvus, PGVector, Neo4j, Neptune, Apache Airflow.
  • AWS & DevOps: EKS, Fargate, Lambda, EC2, ELB/NLB, Glue, Athena, Lake Formation, Terraform, Docker, Puppet.
  • Programming & Full Stack: Python, NumPy, Pandas, Matplotlib, Boto3, React, Next.js, TypeScript/JavaScript.
  • Testing & BI: Ragas, Playwright, Zephyr, Selenium, QuickSight, Tableau.
  • Strong SDLC, DevSecOps, Agile, system design, and production support experience.
More about this job

Responsibilities

Lead the development and delivery of enterprise generative AI products, pilots, and scalable solutions, including LLM pipelines, agentic workflows, Graph RAG, and prompt-based applications. Architect and optimize cloud-native AI solutions on AWS while driving technical strategy, Agile delivery, governance, DevSecOps, and production reliability in collaboration with product, data science, and business teams.

Requirements

Requires 10 or more years of engineering experience, including 1–2 years leading AI initiatives, along with experience in generative AI, LLMs, AI frameworks, databases, orchestration, AWS, and DevOps. Strong programming and full-stack skills, testing and BI experience, and expertise in SDLC, system design, Agile, DevSecOps, and production support are also required.

Skills

  • Generative AI
  • Large Language Models
  • Prompt Engineering
  • Fine-Tuning
  • LangChain
  • LlamaIndex
  • Amazon Bedrock
  • Agentic AI
  • Model Context Protocol
  • Graph RAG
  • AWS
  • Python
  • Terraform
  • Docker
  • DevSecOps
  • Agile

Visa sponsorship

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Categories

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

Keywords

  • Generative AI
  • Large Language Models
  • GPT
  • Claude
  • Gemini
  • LLaMA
  • Prompt Engineering
  • Fine-Tuning
  • LangChain
  • LlamaIndex
  • Amazon Bedrock
  • Agentic AI
  • Model Context Protocol
  • Graph RAG
  • Weaviate
  • Milvus
  • PGVector
  • Neo4j
  • Amazon Neptune
  • Apache Airflow
  • AWS
  • Amazon EKS
  • AWS Fargate
  • AWS Lambda
  • Terraform
  • Docker
  • Python
  • React
  • TypeScript
  • DevSecOps

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