Pay Range: $65.00hr - $70.00hr

Job Overview:

The candidate will lead and actively contribute to the development of scalable Gen AI products, architectures, and cloud-native solutions within an Agile workplace.

Responsibilities:

- 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, prompt-based applications, and emerging technologies.
- Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena.
- Optimize performance of AI products, driving 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 while managing 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 and DevSecOps protocols.

Experience and Skills:

- 8+ years of total experience, with 6+ years of progressive experience in engineering roles,



including at least 1-2 years leading emerging tech or AI initiatives.
- Proficiency with Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques.
- Experience with Agentic AI, MCP, and Graph/RAG architectures.
- Experience with Gen AI Frameworks such as LangChain, LlamaIndex, and Amazon Bedrock.
- Hands-on web application development experience using Next.js, React, and TypeScript/JavaScript.
- Strong knowledge of AWS cloud services including EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, and Lake Formation.
- Proficiency with Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments.
- ETL orchestration experience using Apache Airflow and DAGs.
- Experience with Vector and Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization.
- Advanced Python programming skills (NumPy, Pandas, Matplotlib, Boto3).
- Experience with automated testing frameworks such as Ragas, Playwright, Zephyr, and 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 with BI tools such as QuickSight and Tableau.
- Knowledge of financial markets and enterprise data systems.

Education:

- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.

📌 AI Engineer (Toronto)
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