Senior AI Engineer - Snowflake & Enterprise AI
Listed on 2026-09-01
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Cloud Engineer - Software
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.
Key Responsibilities
- 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.
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, Tensor Flow, 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,…
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