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 effective 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 techniquesAgentic AI, MCP, and Graph/RAG architecturesGen 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 deploymentsVector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimizationAutomated 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 techniquesExperience in BI tools like QuickSight, TableauKnowledge of financial markets and enterprise data systems #J-18808-Ljbffr

📌 Manager, Ai Engineer (Python) (Toronto)
🏢 HRB
📍 Toronto