Gen AI Developer

Job Title: Generative AI Application Developer/GEN AI Developer (8+ Years Experience)

Location: [Dallas, TX]

Rate: [$70/Hour on Corp - Corp]
Job Type: [Third Party, Corp-Corp, W2, Full-Time/Contract]
Industry & Department: [Technology, AI Solutions]

Job Overview:
As a Senior Application Developer, you will be responsible for developing and implementing best practices for AI-driven applications deployment, focusing on automation and artifact generation. You will work with advanced Generative AI models, fine-tuning their outputs, and applying embedding techniques to solve complex problems and drive innovation.

Key Responsibilities:

• AI Model Integration: Evaluate, fine-tune, and implement outputs from Generative AI models, including GPT-3, GPT-4, Google Cloud Platform (Google Cloud Platform) PALM (code bison, text bison), Hugging Face models, AWS Bedrock, Langchain, LlamaIndex, Streamlit, and Chainlit.
• Deployment Automation: Develop and automate processes for deploying AI-driven applications, ensuring scalability, reliability, and efficiency.
• Embedding Techniques: Apply advanced embedding techniques like BERT, Word2Vec, and LLM-based encoders to improve model performance and relevance.
• Collaboration: Work closely with cross-functional teams, including data scientists, engineers, and product managers, to ensure seamless integration of AI models into applications.
• Continuous Improvement: Stay up to date with the latest advancements in AI technologies and implement them to enhance the overall product.
• Documentation & Best Practices: Create and maintain clear documentation of deployment processes, best practices, and model fine-tuning strategies.

Required Skills & Qualifications:

• 8+ years of experience in software/application development with a focus on AI/ML technologies.
• Proven experience with Generative AI models (GPT-3, GPT-4, Google Cloud Platform PALM, Hugging Face, AWS Bedrock, etc.).
• Strong proficiency in deployment automation and artifacts generation for AI-driven applications.
• In-depth knowledge of AI embedding techniques such as BERT, Word2Vec, and LLM-based encoders.
• Hands-on experience with Langchain, LlamaIndex, Streamlit, and Chainlit.
• Expertise in programming languages like Python, TensorFlow, PyTorch, or similar frameworks.
• Familiarity with cloud services (AWS, Google Cloud Platform, Azure) and deployment platforms.
• Strong problem-solving skills and the ability to troubleshoot complex AI model outputs.
• Excellent communication skills and the ability to collaborate with multi-disciplinary teams.