Bayforce

Senior Data Scientist / AI Engineer (GenAI)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist / AI Engineer (GenAI) on a 1-Year CTH contract, offering remote work. Requires 5+ years of experience, hands-on GenAI deployment, strong SQL skills, and cloud experience, preferably with Azure.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
January 28, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Remote
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πŸ“„ - Contract
W2 Contractor
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
United States
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🧠 - Skills detailed
#Snowflake #AI (Artificial Intelligence) #Clustering #Data Science #Databricks #Scala #Azure #AWS (Amazon Web Services) #Databases #Observability #Classification #Cloud #ML (Machine Learning) #SQL (Structured Query Language)
Role description
Senior Data Scientist / AI Engineer (GenAI) Contract-to-Hire | 1-Year CTH Location: Remote Engagement: W2 only – no third parties or vendors We’re looking for a Senior Data Scientist / AI Engineer to help build production-grade GenAI systems for a long-term enterprise client. This is not a research role and not a POC factory. You’ll be designing, deploying, and operating real GenAI agents that integrate with enterprise systems and data platforms at scale. You’ll work closely with engineering and data teams to deliver secure, observable, and reliable AI solutions that are actually used in production. What You’ll Work On β€’ Build and refine GenAI agents that interact with internal enterprise systems β€’ Develop MCP tools, secure integrations, and agent orchestration workflows β€’ Design and maintain knowledge bases, vector search, and retrieval pipelines (RAG) β€’ Implement evaluation frameworks, guardrails, and safety layers for AI agents β€’ Support and scale AI systems across Azure, Snowflake, and Databricks β€’ Apply both modern GenAI techniques and traditional ML to business-critical use cases What We’re Looking For β€’ 5+ years of experience as a Data Scientist or AI Engineer β€’ Hands-on experience building and deploying GenAI / LLM agents in production β€’ Strong knowledge of MCP, tool integrations, and agent orchestration β€’ Experience designing knowledge systems, vector databases, and retrieval pipelines β€’ Comfort with rapid GenAI prototyping (β€œvibe coding”) and production hardening β€’ Cloud experience with Azure (preferred) or AWS β€’ Strong SQL skills and hands-on experience with Snowflake β€’ Experience using Databricks for data and ML workflows β€’ Solid foundation in traditional ML (classification, clustering, etc.) β€’ Experience with MLOps, LLM observability, evals, and safety frameworks What Makes This Role Different β€’ You’ll work on real, production AI systems, not experiments β€’ Strong focus on engineering quality, observability, and scalability β€’ Long-term client with a clear AI roadmap β€’ No third parties or vendors – direct engagement only If you’re excited about building AI systems that actually ship and scale, this role is worth a conversation.