Title: AI Platform Engineer Location: Toronto, Ontario, Canada (4-day onsite/week) Duration: 6 Months Job Description: Lead and actively contribute to the development of AI products, pilots, and solutions, with a focus on clean, maintainable code using Python, React, and AWS tools.

Design, architect, and build scalable Gen AI solutions, including LLM pipelines, Agentic, MCP, Graph/RAG architectures, and prompt-based applications and emerging tech.

Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.

Optimize performance of AI products; drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains.

Work closely with product managers, data scientists, and domain experts to define technical solutions aligned with business needs.

Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization's AI roadmap.

Own end-to-end delivery of Gen AI solutions.

Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban).

Monitor operational metrics and incident data to drive continuous improvement and reliability.

Job Responsibilities: Ensure adherence to governance and Dev

SecOps protocols.



6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives.

Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques Agentic AI, MCP, and Graph/RAG architectures Gen AI Framework (Lang

Chain, Llama

Index, Amazon Bedrock) Web application development using Next.js, React, Type

Script/Java

Script AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation) Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments ETL orchestration using Apache Airflow/DAGs Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4j, Neptune) and query optimization Python programming (Num

Py, Pandas, Matplotlib, Boto3) Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium) Familiarity with SDLC best practices, Dev

SecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).

Knowledge of LLM fine-tuning techniques Experience in BI tools like Quick

Sight, Tableau Knowledge of financial markets and enterprise data systems Education: Bachelor's or Master's degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

📌 AI Platform Engineer (Toronto)
🏢 VDart
📍 Toronto