We are seeking a highly skilled Data Scientist Generative AI Specialist to design, develop, and optimize next-generation AI solutions. The ideal candidate will have hands-on expertise in Generative AI, Agentic AI, LLMs, and NLP, along with a strong background in MLOps and cloud-based AI deployments. This role will focus on building intelligent, scalable AI systems leveraging advanced frameworks, orchestration tools, and cloud services.

Key Responsibilities :

- Design, develop, and deploy generative AI solutions, including LLM-based systems, RAG pipelines, and agentic AI applications.

- Build and optimize prompt engineering strategies, knowledge graphs, embeddings, and semantic search pipelines.

- Implement and manage vector databases (e.g., FAISS, Redis) for scalable search and retrieval tasks.

- Leverage Azure AI tools (Azure OpenAI, Cognitive Services, Azure ML) and orchestration frameworks (e.g., LangChain, Agentic AI frameworks).

- Fine-tune and deploy models using Hugging Face, OpenAI APIs, and related AI platforms.

- Collaborate with engineering teams to integrate AI applications using FastAPI, Databricks, AWS, and MLflow.

- Establish and maintain CI/CD pipelines for ML models, ensuring seamless MLOps and DevOps integration.

- Debug, optimize, and continuously improve AI pipelines, deployments, and end-user performance.

- Stay updated with the latest advancements in AI research, tools, and frameworks.

Required Skills & Qualifications :

- 3+ years of proven experience in Data Science, with a focus on Generative AI, LLMs, NLP, and Agentic AI.

- Hands-on expertise in RAG pipelines, knowledge graphs, embeddings, and semantic search.

- Strong development skills in Python for AI/ML application development.

- Experience with Azure AI tools (Azure OpenAI, Cognitive Services, Azure ML).

- Proficiency in LangChain, Hugging Face, and agentic AI orchestration frameworks.

- Solid experience with MLOps, CI/CD pipelines, AI deployment optimization, and DevOps practices.

- Familiarity with FastAPI, Databricks, AWS, MLflow, Faiss, Redis, and OpenAI APIs.

- Strong problem-solving, debugging, and optimization mindset.

Preferred Qualifications :

- Prior contributions to AI/ML research or open-source projects.

- Experience building enterprise-grade AI solutions for production.

- Knowledge of scalable system design for AI-driven applications.