Key Responsibilities :

- Design and develop GenAI applications using LLMs (OpenAI, Azure OpenAI, Gemini, Llama, etc.).

- Build prompt engineering and optimization strategies for chatbot, agent, and automation use cases.

- Develop and integrate AI pipelines, including embeddings, vector search, RAG (Retrieval-Augmented Generation), and fine-tuning.

- Implement NLP/NLU features such as summarization, classification, entity extraction, and conversation flows.

- Build APIs and microservices to integrate GenAI capabilities with enterprise systems.

- Work closely with data engineering teams to prepare datasets for training, fine-tuning, and evaluation.

- Evaluate model performance, conduct experimentation, and improve accuracy, reliability, and safety.

- Implement AI governance practices including monitoring, logging, and responsible AI compliance.

- Document architecture, workflows, and project deliverables for stakeholders.

Required Skills & Qualifications :

- Bachelors/Masters degree in Computer Science, AI/ML, Data Science, or related field.

- 35+ years of hands-on experience in AI/ML development, with at least 12 years in Generative AI.

- Strong knowledge of:

- Python, PyTorch or TensorFlow

- LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.)

- Vector databases (Pinecone, FAISS, Chroma, Weaviate)

- RAG pipelines and embeddings

- Document processing (PDF, OCR, unstructured data)

- Experience building and deploying AI microservices using FastAPI/Flask.

- Familiarity with cloud platforms (Azure/AWS/GCP) and DevOps tools.

- Understanding of ML lifecycle: data preparation, training, evaluation, deployment.