Key Responsibilities

Architect and implement advanced generative AI solutions, including those for text and image generation, and document/image extraction.
Apply advanced techniques such as Retrieval-Augmented Generation (RAG), fine-tuning, and sophisticated prompt engineering.
Develop and deploy generative AI models, ensuring they meet performance, scalability, and business objectives.
Integrate AI models into products and services by collaborating with data engineers, software developers, and product managers.
Ensure ethical AI development by adhering to industry standards and regulatory requirements.
Utilize data science principles for model enhancement, using statistical analysis and machine learning to improve model accuracy and efficiency.
Build and deploy cloud-native, containerized infrastructure for AI models, using tools like Kubernetes or ECS.
Contribute to prompt engineering and chatbot development when required.

Required Skills

Technical Expertise:

Programming: Python.
AI/ML Frameworks: TensorFlow, PyTorch, or similar.
Gen AI Tools: Experience with LangChain, Azure OpenAI, or open-source LLMs is a significant plus.
Techniques: Strong grasp of RAG, fine-tuning, prompt engineering, and data embeddings.
Data Handling: Data mining, cleansing, and preprocessing of structured and unstructured data.

Architectural & Design:

Problem-Solving:

Collaboration:

GEN AI Architect