Senior Snowflake Cortex AI Engineer

Senior Snowflake Cortex AI Engineer


Location - Onsite (Windsor, CT or New York)


AI Engineer (Snowflake Cortex / LLM Systems)


Role Summary


The AI Engineer is responsible for building and deploying Large Language Model (LLM)-enabled applications and AI pipelines that operate natively within the Snowflake environment. Leveraging Snowflake Cortex, this role will deliver governed, production-grade AI experiences tailored to enterprise standards and requirements.


Key Responsibilities
• Design and deliver comprehensive AI pipelines, covering all stages from data ingestion through retrieval, model inference, and output generation, ensuring scalability for deployment across the organization.
• Develop LLM-based applications, focusing on prompt engineering and optimization to enhance both response quality and the overall effectiveness of AI-driven tasks.
• Implement retrieval-augmented generation (RAG) architectures to improve the reliability and grounding of enterprise information retrieval systems.
• Create AI processing solutions that run directly within Snowflake, utilizing Snowpark (Python) and Snowflake Cortex AI services for seamless integration.
• Integrate both structured and unstructured enterprise data, enabling robust retrieval and response generation within Snowflake-native architectural patterns.
• Employ strategies for hallucination prevention, including grounding methods, validation layers, and structured approaches to retrieval and prompt design.
• Establish AI guardrails and monitoring systems that align with enterprise governance, covering data protection, model behavior oversight, and response validation.
• Operate within Snowflake-specific security frameworks, including role-based access control (RBAC) and secure processing practices.
• Deploy AI solutions into production environments, ensuring robust monitoring, logging, and performance management, while integrating outputs into applications, dashboards, and workflows.
• Optimize costs associated with Snowflake compute and AI workloads by employing efficient retrieval patterns and caching strategies.
• Build and maintain continuous integration/continuous deployment (CI/CD) systems for AI workflows, incorporating automated testing, deployment, and version control for models, prompts, and related processes.


Required Qualifications


Extensive experience with Python, particularly for AI pipeline development, orchestration, and automation.


Advanced proficiency in SQL for querying, transforming, and integrating datasets within Snowflake.
• Familiarity with Python libraries such as LangChain, Pandas, NumPy, and other relevant machine learning frameworks.
• Significant experience with Snowflake Cortex AI services and native Snowflake AI integration patterns.
• Demonstrated success in implementing RAG architectures and reliability controls, focusing on grounding and validation to minimize hallucinations.
• Hands-on experience deploying AI systems into production, including operational monitoring and performance management.