AI Engineer

We are looking for a highly skilled and forward-thinking AI Engineer with deep expertise in Snowflakes Cortex AI , Maya from Mendix , and strong working knowledge of large language models (LLMs) . The ideal candidate has experience developing intelligent AI agents, integrating low-code AI capabilities, and building traditional machine learning solutions. This role offers the opportunity to work at the cutting edge of AI product development and enterprise AI integration. Key Responsibilities: Design, develop, and deploy AI agents using both LLMs and traditional ML approaches Leverage Cortex AI in Snowflake to build and integrate scalable AI/ML models into data pipelines and applications Utilize Maya (Mendix AI) to embed AI features into low-code enterprise applications Evaluate and integrate major LLMs (e.g., OpenAI GPT, Claude, Google Gemini, Mistral, etc.) for various use cases including text summarization, classification, code generation, and chat interfaces Fine-tune and customize foundation models as needed for enterprise tasks Work closely with data engineering and software teams to operationalize AI models in production Monitor model performance and implement improvements and retraining strategies Ensure AI solutions meet security, compliance, and ethical standards Stay current with the latest advancements in AI, ML, and LLM ecosystems Required Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field 2+ years of experience in AI/ML development, with hands-on exposure to deploying production-grade models Hands-on experience with Cortex AI in Snowflake , including model training and inference Proficiency in Maya from Mendix or similar AI-assisted low-code platforms Strong experience with Python, SQL, and AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Experience working with and integrating APIs of LLMs like OpenAI, Hugging Face, or Cohere Proven ability to design and implement AI agents or copilots using tools like LangChain, Semantic Kernel, or RAG pipelines Familiarity with MLOps principles, CI/CD pipelines, and cloud-based ML (AWS, Azure, or GCP) Preferred Qualifications: Experience in data-centric AI and vector search (e.g., Pinecone, FAISS, Weaviate) Experience in prompt engineering and LLM evaluation Knowledge of security and governance best practices for enterprise AI Contributions to AI open-source projects or publications in the field Certifications in Snowflake, Mendix, or cloud-based AI platforms