Lorven Technologies Inc.
Data and GenAI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Data and GenAI Engineer (Finance Domain) in Dallas, TX, on a long-term contract. Key skills required include GraphDB, VectorDB, data pipelines, AI, Scala, and compliance in financial data governance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 15, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Knowledge Graph #Data Pipeline #AI (Artificial Intelligence) #ML (Machine Learning) #Cloud #Compliance #Data Governance #Scala
Role description
Our client is looking for a Sr Data and GenAI Engineer (Finance Domain) with a Long-Term Contract project in Dallas, TX below is the detailed requirement.
Job Title: Sr Data and GenAI Engineer (Finance Domain)
Location: Dallas, TX
Contract
Key Responsibilities:
• Design and implement GraphDB and VectorDB solutions to store, query, and retrieve structured and unstructured financial data.
• Build knowledge graph pipelines integrating multiple data sources to support LLM fine-tuning and retrieval-augmented generation workflows.
• Set up scalable data pipelines for model training, embedding generation, and data pre-processing
• Collaborate with AI researchers and ML engineers to prepare data and infrastructure for fine-tuning open-source or proprietary LLMs.
• Deploy and optimize model hosting for fast inference on on-prem or cloud GPU servers.
• Ensure data governance, lineage and compliance with internal and regulatory standards.
Our client is looking for a Sr Data and GenAI Engineer (Finance Domain) with a Long-Term Contract project in Dallas, TX below is the detailed requirement.
Job Title: Sr Data and GenAI Engineer (Finance Domain)
Location: Dallas, TX
Contract
Key Responsibilities:
• Design and implement GraphDB and VectorDB solutions to store, query, and retrieve structured and unstructured financial data.
• Build knowledge graph pipelines integrating multiple data sources to support LLM fine-tuning and retrieval-augmented generation workflows.
• Set up scalable data pipelines for model training, embedding generation, and data pre-processing
• Collaborate with AI researchers and ML engineers to prepare data and infrastructure for fine-tuning open-source or proprietary LLMs.
• Deploy and optimize model hosting for fast inference on on-prem or cloud GPU servers.
• Ensure data governance, lineage and compliance with internal and regulatory standards.
