Collaborate closely with business stakeholders to understand requirements, identify opportunities, and translate business problems into AI-driven solutions.

Design, develop, and rapidly prototype Generative AI applications, Proofs of Concept (PoCs), and production-ready solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern AI frameworks.

Build and optimize AI workflows by integrating LLMs, vector databases, APIs, enterprise data sources, and orchestration frameworks to deliver scalable solutions.

Apply prompt engineering techniques, model evaluation strategies, and iterative optimization to improve the accuracy, reliability, and effectiveness of AI applications.

Develop AI-powered automation solutions that streamline business processes, enhance decision-making, and improve operational efficiency.

Perform AI solution assessments, model benchmarking, and quality evaluations using quantitative and qualitative metrics to recommend optimal approaches.

Integrate AI solutions with structured and unstructured data sources, including data preparation, validation, annotation, augmentation, and migration activities.

Leverage AI-assisted development tools and modern engineering practices to accelerate solution delivery while maintaining code quality and scalability.

Collaborate with cross-functional teams including business, product, engineering, and data teams to deliver customer-centric AI solutions.

Stay current with advancements in Generative AI, Machine Learning, LLMs, and emerging AI technologies, continuously identifying opportunities to improve solution capabilities.