Key Responsibilities :

- Design, develop, and deploy Generative AI applications using LLMs and modern AI frameworks.

- Build and optimize RAG-based solutions to enable context-aware information retrieval and generation.

- Develop AI agents and agentic AI workflows to automate complex tasks and business processes.

- Implement effective prompt engineering techniques to improve model accuracy, relevance, and response quality.

- Develop AI-powered applications, chatbots, virtual assistants, and intelligent automation solutions.

- Integrate LLMs, APIs, vector databases, and external data sources into AI applications.

- Evaluate model performance, troubleshoot issues, and optimize AI solutions for accuracy, scalability, and reliability.

- Collaborate with cross-functional teams and stakeholders to understand requirements and deliver effective AI solutions.

- Stay updated on emerging Generative AI technologies, frameworks, tools, and industry best practices.

Required Skills & Qualifications :

- Strong programming and coding proficiency in Python is mandatory.

- Strong understanding of Generative AI concepts and Large Language Models (LLMs).

- Hands-on knowledge of Retrieval-Augmented Generation (RAG) and semantic search.

- Understanding of AI agents, agentic AI architectures, and multi-step AI workflows.

- Knowledge of prompt engineering techniques and LLM application development.

- Familiarity with APIs, data processing, and integrating AI models into applications.

- Strong analytical, problem-solving, and debugging skills.

- Ability to learn new technologies quickly and work in a collaborative environment.