Senior AI Engineer - Snowflake & Enterprise AI

Contract (11 months 28 days)

Published 29 days ago

AI

Snowflake

SQL

RAG

Snowflake Cortex

Cortex AI

This is a temporary contractor position for an exiting vacancy.

Hybrid - 2 times a week in office

We are looking for an innovative and experienced AI Engineer with strong Snowflake expertise to design, build, and product ionize 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.

Design and develop scalable AI and ML solutions using Snowflake and Snowflake Cortex
.

Build and product ionize 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.

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.

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, Tensor Flow, or Hugging Face
.

Experience with MLOps, LLMOps, model evaluation, observability, and AI application monitoring.

Knowledge of enterprise APIs, microservices, REST APIs, and…