

Bayforce
Senior Data Scientist / AI Engineer (GenAI)
β - 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.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
January 28, 2026
π - Duration
More than 6 months
-
ποΈ - Location
Remote
-
π - Contract
W2 Contractor
-
π - Security
Unknown
-
π - Location detailed
United States
-
π§ - 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 β no third parties or vendors
Weβre 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. Youβll be designing, deploying, and operating real GenAI agents that integrate with enterprise systems and data platforms at scale.
Youβll work closely with engineering and data teams to deliver secure, observable, and reliable AI solutions that are actually used in production.
What Youβll 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 Weβre 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 (βvibe codingβ) 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’ Youβll 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 β direct engagement only
If youβre excited about building AI systems that actually ship and scale, this role is worth a conversation.
Senior Data Scientist / AI Engineer (GenAI)
Contract-to-Hire | 1-Year CTH
Location: Remote
Engagement: W2 only β no third parties or vendors
Weβre 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. Youβll be designing, deploying, and operating real GenAI agents that integrate with enterprise systems and data platforms at scale.
Youβll work closely with engineering and data teams to deliver secure, observable, and reliable AI solutions that are actually used in production.
What Youβll 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 Weβre 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 (βvibe codingβ) 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’ Youβll 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 β direct engagement only
If youβre excited about building AI systems that actually ship and scale, this role is worth a conversation.






