Pacer Group
GenAI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GenAI Engineer in Houston, TX (Hybrid – 3 days onsite) with a contract length of unspecified duration, offering $60-65/hr. Requires 5+ years in Python, 2+ years in GenAI/LLM development, and cloud experience (GCP/Azure).
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
520
-
🗓️ - Date
April 9, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Houston, TX
-
🧠 - Skills detailed
#Langchain #DevOps #Docker #Python #GCP (Google Cloud Platform) #Terraform #Cloud #Azure #Kubernetes #Scala #AI (Artificial Intelligence) #Databases
Role description
GenAI Engineer
AI Developer (GenAI / LLM Applications)
Houston, TX (Hybrid – 3 days onsite)
Rate: $60-65/hr
Role Overview
We are seeking an Applied AI Engineer to design and build scalable, production-grade GenAI applications. This role focuses on developing LLM-powered solutions using RAG, agent workflows, and modern AI orchestration frameworks.
Key Responsibilities
• Build and deploy GenAI applications using LLMs, RAG, and prompt engineering
• Design retrieval pipelines with embeddings and vector databases (FAISS, Pinecone, etc.)
• Develop APIs and backend services in Python
• Implement agent workflows using LangChain, LangGraph, or LlamaIndex
• Deploy scalable solutions on GCP/Azure using Docker and Kubernetes
Required Skills
• 5+ years Python/software engineering experience
• 2+ years hands-on GenAI/LLM application development
• Strong experience with RAG, embeddings, and vector databases
• Experience with LangChain / LangGraph / LlamaIndex
• Cloud experience (GCP or Azure) + Docker/Kubernetes
Nice to Have
• DevOps (Terraform, CI/CD pipelines)
• Experience building production AI systems
GenAI Engineer
AI Developer (GenAI / LLM Applications)
Houston, TX (Hybrid – 3 days onsite)
Rate: $60-65/hr
Role Overview
We are seeking an Applied AI Engineer to design and build scalable, production-grade GenAI applications. This role focuses on developing LLM-powered solutions using RAG, agent workflows, and modern AI orchestration frameworks.
Key Responsibilities
• Build and deploy GenAI applications using LLMs, RAG, and prompt engineering
• Design retrieval pipelines with embeddings and vector databases (FAISS, Pinecone, etc.)
• Develop APIs and backend services in Python
• Implement agent workflows using LangChain, LangGraph, or LlamaIndex
• Deploy scalable solutions on GCP/Azure using Docker and Kubernetes
Required Skills
• 5+ years Python/software engineering experience
• 2+ years hands-on GenAI/LLM application development
• Strong experience with RAG, embeddings, and vector databases
• Experience with LangChain / LangGraph / LlamaIndex
• Cloud experience (GCP or Azure) + Docker/Kubernetes
Nice to Have
• DevOps (Terraform, CI/CD pipelines)
• Experience building production AI systems
