Manager, AI Engineer (Python)

HRB; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

HRB is seeking a Manager Technology to lead hands-on Python-based engineering teams focused on Gen AI products and scalable AI solutions in a cloud-native AWS environment.

You will mentor engineers, define technical solutions aligned with business needs, and drive the AI roadmap. Strong experience in Gen AI, LLMs, prompt engineering, and modern tooling is essential.

Qualifications

• 6+ years of progressive engineering experience with 1–2 years leading AI initiatives.
• Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques.
• Agentic AI, MCP, and Graph/RAG architectures.
• Gen AI Frameworks (LangChain, LlamaIndex, Amazon Bedrock).
• AWS cloud services and containerized deployments (EC2, EKS, Fargate, Lambda).
• Infrastructure as Code (Terraform, Docker).
• Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune).
• Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium).
• SDLC/DevSecOps/Agile Scrum/Kanban practices.

Responsibilities

• Lead and contribute to AI product development and pilots with Python, React, and AWS tools.
• Architect scalable Gen AI solutions including LLM pipelines and graph-based architectures.
• Own end-to-end delivery, timelines, and milestones using Agile methods.

Skills

Leadership

Gen AI strategy

AI product delivery

Cross-functional collaboration

Agile/Scrum/Kanban

Prompt engineering

LLM fine tuning

Bi tools (QuickSight/Tableau)

Cloud architecture

Governance/DevSecOps

Tools

AWS (EC2, EKS, Lambda, Fargate, Athena, Glue)

Terraform

Docker

Weaviate/Milvus/Neo4J/Neptune

LangChain/LlamaIndex/Amazon Bedrock

Ragas/Playwright/Zephyr/Selenium

JIRA/Confluence/JIRA Align

Job description

As a Manager Technology, you will lead and manage and hands on Python-based engineering teams, ensuring the successful delivery of high-quality, scalable, and efficient solutions. You will work closely with cross-functional teams to drive technical excellence, mentor engineers, and contribute to the strategic direction of technology initiatives.

• 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.
• Ensure adherence to governance, DevSecOps protocols.
  

Experience/Skiils:

• 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)
• AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation)
• Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments
• Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization
• 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