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AI Engineer - Snowflake & Enterprise AI

  • Source: LinkedIn
  • Tundra Technical Solutions
  • On-site
  • Toronto
  • Mid level

Job Description

We are 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.

You will play a key role in developing scalable AI solutions using Snowflake, Snowflake Cortex AI, SQL, Python, machine learning, and Generative AI technologies , while partnering with data and AI engineers, data scientists, architects, governance and cybersecurity teams, and business stakeholders.

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. …

Skills

  • Snowflake
  • cortex
  • Python
  • microsoft-azure
  • azure-data-factory
  • microsoft-fabric
  • Scikit-learn
  • PyTorch
  • Tensorflow
  • hugging-face
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