Senior Data Scientist - GenAI

• 6+ years of experience in Data Science, AI Engineering, Machine Learning, or a related field.
• 4+ years of professional Python development experience.
• 2+ years of hands-on experience with LLMs / Generative AI , preferably with RAG-based solutions.
• Strong knowledge of Python, LLMs, RAG, and Generative AI .
• Practical experience with LangChain, LlamaIndex, LangGraph , or similar frameworks.
• Experience with AI Agents / Agentic AI ; MCP experience is a strong advantage.
• Knowledge of vector databases, hybrid search, reranking, and LLM evaluation .
• Experience with model fine-tuning , such as LoRA, QLoRA, or SFT.
• Experience with at least one major cloud platform: Azure, AWS, or GCP .
• Familiarity with Docker, Kubernetes, and CI/CD .
• Good understanding of AI/ML architectures and production deployment practices .
• Excellent English communication skills .

Nice to Have

• Experience with Spark / Databricks .
• Experience with GitHub Actions, GitLab CI, or Azure DevOps .
• Experience with multi-agent systems and agentic AI workflows .
• Experience building scalable, production-grade AI systems.
• Experience with multimodal AI models .

We are looking for an experienced professional to join projects focused on Generative AI, LLMs, RAG, and AI Agents . The rol

,[Design and develop production-grade solutions using LLMs and Generative AI., Build and optimize RAG systems, including vector search, hybrid search, reranking, and query optimization., Develop AI Agents and agentic AI solutions., Work with frameworks such as LangChain, LlamaIndex, LangGraph, or similar technologies., Work with MCP to integrate AI agents with external tools and systems., Select appropriate models and develop prompt engineering and fine-tuning strategies, including LoRA/QLoRA/SFT., Implement LLM evaluation, validation, guardrails, and quality control mechanisms., Develop APIs/backend components and integrate AI solutions with existing systems., Contribute to technical architecture and technology selection., Collaborate with engineers, developers, and product teams., Share knowledge and support less experienced team members.] Requirements: Data science, AI, Machine learning, Python, Cloud platform, AWS, Docker, Kubernetes, Spark, Databricks, GitHub, GitLab CI, Azure DevOps