Key Responsibilities
- Lead the design, development, and deployment of scalable GenAI solutions tailored to organizational needs.
- Architect and implement N-tiered and multi-tier applications , ensuring high performance, scalability, and maintainability.
- Drive the development of AI / GenAI systems , ensuring they meet enterprise-grade standards in security, efficiency, and reliability.
- Lead end-to-end enterprise implementations for AI / GenAI projects, including architecture, infrastructure, security, and MLOps / GenAIOps .
- Work with RAG (Retrieval-Augmented Generation) technologies, LLM frameworks , embedding models , and vector databases .
- Integrate LLM APIs and registries (e.g., Hugging Face) to enhance AI solution capabilities.
- Design and develop data processing and analytics systems using Python frameworks such as Django, Flask, Django REST, or FastAPI .
- Perform hands-on coding and oversee all phases of the software development lifecycle (SDLC) from concept to deployment.
- Collaborate with cross-functional teams and internal stakeholders to align GenAI initiatives with business goals.
- Lead and mentor junior engineers, fostering a culture of innovation and continuous learning.
- Troubleshoot, optimize, and maintain complex systems and applications to ensure seamless performance.
Skills Required
Artificial Intelligence, Machine Learning, Llm