Junior Generative AI Engineer

About the Role

We are seeking a driven Junior Generative AI Engineer to join our team in Brampton. This position involves contributing to the design, creation, and deployment of AI-powered agentic applications, AI agents, and Retrieval Augmented Generation (RAG) systems. The successful candidate will play an integral role in merging Generative AI technologies with enterprise data platforms, ensuring solutions are secure, resilient, and commercially impactful.

Key Responsibilities

• Architect, construct, test, and launch AI-powered agentic applications and AI agents.
• Enhance and build Generative AI and machine learning systems that create measurable business value.
• Implement RAG techniques, prompt engineering, and AI workflow automation methodologies.
• Create reusable APIs, services, and components that facilitate faster AI deployment.
• Integrate AI solutions seamlessly with enterprise applications, data platforms, and operational processes.
• Design and optimize data pipelines and services supporting AI initiatives.
• Participate in enterprise AI platform development, including Gemini Enterprise, Vertex AI, Databricks, and related technologies.
• Apply governance principles, security protocols, privacy regulations, and Responsible AI frameworks to AI projects.
• Support AI production deployment, monitoring, troubleshooting, and ongoing refinement.
• Document technical designs clearly and coordinate with multidisciplinary teams to ensure project success.

Qualifications and Experience

• Bachelor's degree in Computer Science, Software Engineering, Data Science, AI, IT, Engineering, or an equivalent qualification/experience.
• Certifications related to Google Cloud, Vertex AI, ML Engineering, Data Engineering, or other cloud AI specialties.
• Practical experience developing enterprise copilots, chatbots, document intelligence solutions, workflow assistants, or agentic AI applications.
• Familiarity with observability, quality evaluation, red-teaming, hallucination mitigation, and security controls for AI systems.
• Over two years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or similar technical roles.

Technical Skills

• Proficiency in Python and SQL programming, API development, Git version control, CI/CD pipelines, testing, and general software engineering best practices.
• Hands-on knowledge of Generative AI, large language models (LLMs), RAG, vector search, embeddings, prompt engineering, AI agents, and model evaluation methodologies.
• Experience with Google Cloud Platform, Vertex AI, Gemini Enterprise, or similar cloud AI environments.
• Exposure to Databricks, Spark/PySpark, Delta Lake, Unity Catalog, MLflow, and contemporary lakehouse architecture.
• Familiarity with AI tools and frameworks such as LangChain, LangGraph, CrewAI, AutoGen, FastAPI, Streamlit, Docker, Kubernetes, or comparable technologies is advantageous.
• Understanding of data governance principles, data quality management, metadata and lineage tracking, security, privacy protocols, and adherence to Responsible AI standards.

Soft Skills

• Excellent problem-solving aptitude, capable of translating business requirements into scalable, pragmatic engineering solutions.
• Strong communication abilities, able to articulate AI concepts, risks, constraints, and trade-offs to both technical and non-technical audiences.
• A proactive ownership approach emphasizing reliable delivery, thorough documentation, and consistent improvement.
• Collaborative team player experienced in working across data, AI, infrastructure, security, governance, architecture, business, and vendor groups.
• A keen interest in continuous learning about emerging AI technologies combined with sound enterprise judgment.