Sr AI Engineer
Lead the design and development of scalable Generative AI solutions, including LLM pipelines and Agentic architectures. Collaborate with cross-functional teams to align technical AI roadmaps with business needs and ensure end-to-end delivery.
- On-site
- Toronto, ON
- Posted Aug 13, 2026
- Apply by Feb 9, 2027
- 1 position
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Job summary
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) 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, Project Code :
What you’ll do
Lead the design and development of scalable Generative AI solutions, including LLM pipelines and Agentic architectures. Collaborate with cross-functional teams to align technical AI roadmaps with business needs and ensure end-to-end delivery.
Requirements
Requires over 6 years of engineering experience, with at least 1-2 years leading AI initiatives. Proficiency in Python, AWS cloud services, and Gen AI frameworks like LangChain or Bedrock is essential.
Listed skills
- PythonPreferred
- ReactPreferred
- Amazon Web ServicesPreferred
- Next.jsPreferred
- TypeScriptPreferred
- TerraformPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- React
- AWS
- Generative AI
- LLM Pipelines
- LangChain
- LlamaIndex
- Amazon Bedrock
- Next.js
- TypeScript
- Terraform
- Apache Airflow
- Vector Databases
- Graph Databases
- Prompt Engineering
- DevSecOps
Job areas
- Software
- Technology
- Engineering
- Data & Analytics
- Consulting
Additional details
- Minimum experience
- 5+ years
- Apply by
- Feb 9, 2027
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available