AI Lead (Generative AI) at Diverse Lynx in Irving
- Company: Diverse Lynx
- Location: Irving
- Posted: Sep 24, 2026
- Type: Full-time
- Salary: $80/hr
- Experience: 4+ years
Overview
Location: Irving, TX OR Tampa, FL Rate: $80/hr • Contribute to prompt engineering and development of AI-powered workflows • Assist with the deployment, monitoring, and maintenance of AI models in production environments.
Job description
- Location: Irving, TX OR Tampa, FL
- Rate: $80/hr
Responsibilities
- • Contribute to prompt engineering and development of AI-powered workflows
- • Assist with the deployment, monitoring, and maintenance of AI models in production environments.
- • Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities.
- • Perform data preprocessing, feature engineering, and API development for AI applications.
- • Participate in code reviews, testing, and documentation to ensure quality and reliability.
- • Stay updated with advancements in GenAI and share relevant learnings with the team.
Requirements
- • Familiarity with LLMs, prompt engineering, and workflow orchestration.
- • Exposure to RAG systems and basic knowledge of hybrid search techniques.
- • Exposure to Multi-Agent systems.
- • Understanding of model deployment and containerization (Docker).
- • Proficiency in Python for AI development, data preprocessing, and scripting.
- • Experience with generative AI tools (LanEligible to workhain, Hugging Face, LlamaIndex) is a plus.
- • Understanding of version control systems (Git).
- • Awareness of AI compliance, data privacy, and responsible AI principles.
- • Hands-on experience with at least one major machine learning framework (PyTorch, TensorFlow, Keras). (Advantageous)
- • Strong teamwork and communication abilities.
- • Willingness to learn new AI/ML technologies and frameworks.
- • Analytical mindset and attention to detail.
- • Openness to feedback and continuous improvement.
Skills
Required
- LLMs
- Prompt engineering
- Workflow orchestration
- RAG systems
- Hybrid search techniques
- Multi-Agent systems
- Model deployment
- Containerization (Docker)
- Python
- Version control systems (Git)
- AI compliance
- Data privacy