AI Platform Engineer (Client: Canada Pension Plan Investment Board) [Location: Toronto, Ontario, Canada (4-day onsite/week)]

 Location: Toronto, Ontario, Canada (4-day onsite/week)

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 DevSecOps 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 (LangChain, LlamaIndex, Amazon Bedrock)

·       Web application development using Next.js, React, TypeScript/JavaScript

·       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 (NumPy, Pandas, Matplotlib, Boto3)

·       Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium)

·       Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align).

·       Knowledge of LLM fine-tuning techniques

·       Experience in BI tools like QuickSight, 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.