Senior Generative AI Engineer (6+ Years Experience)

About the Role

We are seeking a highly experienced Senior Generative AI Engineer to lead the architecture, development, and scaling of our enterprise-grade Generative AI and Agentic solutions. Based in our Brampton office, you will drive the integration of LLMs with complex enterprise data structures, lead technical designs, and establish best practices for AI governance, safety, and production reliability.

Key Responsibilities

AI Engineering

Design, develop, test, and deploy Agentic AI-powered applications and AI agents. Build and enhance Generative AI and machine learning solutions that deliver business value. Implement Retrieval Augmented Generation (RAG), prompt engineering, and AI workflow automation patterns. Develop reusable APIs, services, and components to accelerate AI delivery.

Data & Platform Integration

Integrate AI solutions with enterprise applications, data platforms, and business processes. Develop and optimize data pipelines and services that support AI applications. Contribute to enterprise AI platforms including Gemini Enterprise, Vertex AI, Databricks, and related technologies.

Governance & Operations

Apply AI governance, security, privacy, and Responsible AI standards. Support production deployment, monitoring, troubleshooting, and continuous improvement of AI solutions. Document technical designs and collaborate with cross-functional teams to ensure successful delivery.

Requirements

Education & Experience

Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology, Engineering, or a related field (equivalent experience considered). Google Cloud, Vertex AI, ML Engineer, Data Engineer, or related cloud / AI certifications. Extensive experience building enterprise-scale copilots, chatbots, document intelligence solutions, workflow assistants, or agentic applications. Deep experience implementing observability, quality evaluation, red-teaming, hallucination mitigation, and safety controls for AI systems. 6+ years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technology delivery roles.

Technical Skills

Mastery of programming in Python and SQL; expert experience with APIs, Git, CI/CD, testing, and modern software engineering practices. Expertise in Generative AI, LLMs, RAG, vector search, embeddings, prompt engineering, agents, and model evaluation. Strong hands-on experience with Google Cloud Platform, Vertex AI, Gemini Enterprise, or comparable cloud AI platforms is preferred. Strong experience with Databricks, Spark / PySpark, Delta Lake, Unity Catalog, MLflow, and modern lakehouse patterns is preferred. Familiarity with AI frameworks and tools such as LangChain, LangGraph, CrewAI, AutoGen, FastAPI, Streamlit, Docker, Kubernetes, or related technologies is an asset. Solid understanding of data governance, data quality, metadata, lineage, security, privacy, and Responsible AI practices.

Soft Skills

Strong problem-solving skills with the ability to translate complex business needs into practical, scalable engineering solutions. Clear, executive-level communication skills, including the ability to explain AI concepts, risks, limitations, and trade-offs to technical and non-technical stakeholders. Demonstrated ownership mindset with a focus on delivery, production reliability, documentation, and continuous improvement. Ability to collaborate and influence across data, AI, platform, cybersecurity, governance, architecture, business, and vendor teams. Curiosity and a learning mindset to keep pace with emerging AI technologies while applying sound enterprise judgment.