Data Science & Generative AI Engineer

Job Description

As a Senior Data Science & Generative AI Engineer, you will be responsible for designing and developing AI-driven applications leveraging Large Language Models (LLMs) and agentic workflows. Your role will involve building scalable, production-grade systems using modern AI frameworks and backend technologies.Key Responsibilities:- Design and develop AI-driven and Data Science powered applications using LLMs and agentic workflows.- Build and optimize Retrieval-Augmented Generation (RAG) systems.- Develop semantic layers and integrate knowledge graphs for structured reasoning.- Design, build, test, and deploy backend services and REST APIs using Python and FastAPI.- Implement and orchestrate workflows using LangGraph.- Integrate AI systems with external services and APIs.- Ensure code quality, scalability, reliability, and performance in production environments.- Participate in code reviews, enforce coding standards, and follow best practices.- Stay updated with emerging AI tools, frameworks, and LLMOps best practices.Required Skills:- 10 years of experience in Data Science, Machine Learning, or Artificial Intelligence.- Strong hands-on experience with Large Language Models (LLMs) and agentic workflows.- Proven expertise in LangGraph for workflow orchestration.- Extensive experience in building RAG pipelines.- Knowledge of semantic layers and knowledge graphs.- Strong proficiency in Python and FastAPI.- Solid understanding of SQL and NoSQL databases with query optimization skills.- Ability to write production-grade, scalable, and maintainable code.- Experience with Git workflows, pull request reviews, and CI/CD pipelines.- Strong foundation in API design, system architecture, and software design patterns.Good to Have:- Experience with LLMOps, observability, and model lifecycle management.- Exposure to vector databases and advanced retrieval strategies.- Cloud deployment experience (AWS / Azure / GCP). As a Senior Data Science & Generative AI Engineer, you will be responsible for designing and developing AI-driven applications leveraging Large Language Models (LLMs) and agentic workflows. Your role will involve building scalable, production-grade systems using modern AI frameworks and backend technologies.Key Responsibilities:- Design and develop AI-driven and Data Science powered applications using LLMs and agentic workflows.- Build and optimize Retrieval-Augmented Generation (RAG) systems.- Develop semantic layers and integrate knowledge graphs for structured reasoning.- Design, build, test, and deploy backend services and REST APIs using Python and FastAPI.- Implement and orchestrate workflows using LangGraph.- Integrate AI systems with external services and APIs.- Ensure code quality, scalability, reliability, and performance in production environments.- Participate in code reviews, enforce coding standards, and follow best practices.- Stay updated with emerging AI tools, frameworks, and LLMOps best practices.Required Skills:- 10 years of experience in Data Science, Machine Learning, or Artificial Intelligence.- Strong hands-on experience with Large Language Models (LLMs) and agentic workflows.- Proven expertise in LangGraph for workflow orchestration.- Extensive experience in building RAG pipelines.- Knowledge of semantic layers and knowledge graphs.- Strong proficiency in Python and FastAPI.- Solid understanding of SQL and NoSQL databases with query optimization skills.- Ability to write production-grade, scalable, and maintainable code.- Experience with Git workflows, pull request reviews, and CI/CD pipelines.- Strong foundation in API design, system architecture, and software design patterns.Good to Have:- Experience with LLMOps, observability, and model lifecycle management.- Exposure to vector databases and advanced retrieval strategies.- Cloud deployment experience (AWS / Azure / GCP).

Keyskills :
Data ScienceMachine LearningArtificial IntelligencePythonSQLsystem architecturesoftware design patternsLarge Language Models LLMsagentic workflowsLangGraphRAG pipelinessemantic layersknowledge graphsFastAPINoSQL databasesGit workflowsCICD