AI Engineer with Snowflake Expertise

Our client is looking for an innovative and experienced AI Engineer with strong Snowflake expertise to design, build, and productionize enterprise-grade AI and machine learning solutions. In this role, you will work at the intersection of data engineering, AI/ML, Generative AI, and cloud platforms, enabling business teams to leverage trusted enterprise data to drive intelligent decision-making and automation.

Start Date: August 31, 2026 End Date: August 27, 2027 Duration: 1 year Location: Toronto/hybrid model (approx. 2 days onsite)

Key Responsibilities

• Design and develop scalable AI and ML solutions using Snowflake and Snowflake Cortex.
• Build and productionize Generative AI applications, including RAG (Retrieval-Augmented Generation), enterprise AI assistants, intelligent agents, and natural language interfaces.
• Leverage Snowflake Cortex AI capabilities, including LLMs, embeddings, vector search, semantic search, and AI functions.
• Develop data pipelines and AI workflows that integrate structured and unstructured enterprise data.
• Implement RAG architectures, including document ingestion, chunking, embedding generation, vector search, retrieval, re-ranking, and prompt engineering.
• Build and optimize machine learning models and AI solutions using Python, SQL, and cloud-based AI/ML services.
• Develop secure and scalable AI solutions aligned with enterprise architecture, data governance, privacy, and responsible AI standards.
• Collaborate with data engineers to ensure high-quality, governed, and AI-ready data.
• Partner with business stakeholders to translate complex business problems into practical AI solutions with measurable business value.
• Evaluate emerging AI technologies, models, and frameworks and recommend appropriate solutions for enterprise adoption.
• Monitor and optimize AI applications for performance, scalability, reliability, cost, and model quality.
• Implement evaluation frameworks and monitoring for Generative AI applications, including accuracy, relevance, hallucination, latency, and responsible AI metrics.
• Contribute to reusable AI frameworks, patterns, APIs, and engineering standards to accelerate enterprise AI adoption.
• Support the transition of AI prototypes and proof-of-concepts into secure, production-ready enterprise solutions.

Required Qualifications

• Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related technical field.
• 7+ years of experience in software engineering, data engineering, machine learning engineering, or AI engineering.
• Strong hands-on experience with Snowflake, including Snowflake architecture, SQL, data modeling, and performance optimization.
• Experience building AI/ML or Generative AI solutions using enterprise data platforms.
• Strong programming skills in Python and SQL.
• Experience with LLMs, prompt engineering, embeddings, vector databases/search, RAG, and Generative AI application development.
• Experience working with cloud platforms such as Microsoft Azure.
• Experience developing production-grade data and AI pipelines.
• Understanding of data governance, security, privacy, access controls, and responsible AI practices.
• Strong problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Must have experience with Snowflake Cortex, Cortex AI, Cortex Search, Cortex Analyst, or Snowpark.
• Must have experience with Snowflake Intelligence and AI agent architectures.
• Must have experience building AI agents using platforms such as Microsoft Copilot Studio, Azure AI Foundry.
• Must have experience with Azure Data Factory, Microsoft Fabric.
• Experience with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or Hugging Face.
• Experience with MLOps, LLMOps, model evaluation, observability, and AI application monitoring.
• Knowledge of enterprise APIs, microservices, REST APIs, and event-driven architectures.
• Experience working in highly regulated industries such as financial services, utilities, healthcare, or government.
• Experience with CI/CD, build enterprise end-to-end AI solution.
• Snowflake certifications are an asset.

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