

Jobs via Dice
Generative AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Generative AI Engineer in Dallas, TX, on a contract basis. Candidates should have 4-8 years of software engineering experience, with 4-5 years in AI/ML or GenAI systems, and proficiency in Python and LLM frameworks.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
November 13, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Python #GCP (Google Cloud Platform) #Scala #Deployment #AI (Artificial Intelligence) #Cloud #Langchain #ML (Machine Learning) #DevOps #Automation #GIT
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Envision Technology Solutions, is seeking the following. Apply via Dice today!
Job Title: Generative AI Engineer
Location: Dallas, TX
Job Type: - Contract
On-Site interview at Richardson, TX
Job Description:-
Key Responsibilities
Design, develop, and deploy agentic AI systems leveraging LLMs and modern AI
frameworks.
Integrate GenAI models into full-stack applications and internal workflows.
Collaborate on prompt engineering, model fine-tuning, and evaluation of generative
outputs.
Build reusable components and services for multi-agent orchestration and task
automation.
Optimize AI inference pipelines for scalability, latency, and cost efficiency.
Participate in architectural discussions, contributing to the pod's technical roadmap.
Core Skills & Experience
Must Haves
4 8 years of software engineering experience with at least 4-5 years in AI/ML or GenAI
systems in production
Hands-on experience with Python only for AI/ML model integration.
Experience with LLM frameworks (LangChain, LlamaIndex is a must
Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment
practices.
Nice-to-Have
Familiarity with Google Cloud Platform (Google Cloud Platform) - especially Vertex AI, Cloud Run, and
GKE.
Experience building AI APIs, embeddings, vector search, and integrating them into
applications.
Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with
OpenAI APIs.
Exposure to multi-modal AI systems (text, image, or voice).
Familiarity with Low-Code/No-Code tools (e.g., AppSheet) for workflow integration.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Envision Technology Solutions, is seeking the following. Apply via Dice today!
Job Title: Generative AI Engineer
Location: Dallas, TX
Job Type: - Contract
On-Site interview at Richardson, TX
Job Description:-
Key Responsibilities
Design, develop, and deploy agentic AI systems leveraging LLMs and modern AI
frameworks.
Integrate GenAI models into full-stack applications and internal workflows.
Collaborate on prompt engineering, model fine-tuning, and evaluation of generative
outputs.
Build reusable components and services for multi-agent orchestration and task
automation.
Optimize AI inference pipelines for scalability, latency, and cost efficiency.
Participate in architectural discussions, contributing to the pod's technical roadmap.
Core Skills & Experience
Must Haves
4 8 years of software engineering experience with at least 4-5 years in AI/ML or GenAI
systems in production
Hands-on experience with Python only for AI/ML model integration.
Experience with LLM frameworks (LangChain, LlamaIndex is a must
Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment
practices.
Nice-to-Have
Familiarity with Google Cloud Platform (Google Cloud Platform) - especially Vertex AI, Cloud Run, and
GKE.
Experience building AI APIs, embeddings, vector search, and integrating them into
applications.
Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with
OpenAI APIs.
Exposure to multi-modal AI systems (text, image, or voice).
Familiarity with Low-Code/No-Code tools (e.g., AppSheet) for workflow integration.






