Senior Data Scientist Engineer

Who you are

• Master’s degree in Artificial Intelligence, Computer Science, Data Science, or related field
• Minimum 3-years experience in relevant fields
• Strong programming skills in Python, Java, SQL and data processing
• Experience working with structured and unstructured data
• Knowledge of machine learning, deep learning, NLP, and LLM systems
• Deep knowledge of MCP and A2A protocols
• Experience with model training, evaluation, and experimentation
• Familiarity with prompt engineering, agent-based architectures, and retrieval systems
• Experience with APIs, distributed systems, and cloud platforms
• Ability to apply data science and AI techniques to real-world business problems

What the job involves

• This role designs, develops, and deploys scalable AI and data-driven solutions leveraging machine learning, deep learning, natural language processing (NLP), and large language models (LLMs)
• The position is responsible for building intelligent agent architectures, prompt-driven workflows, and retrieval-augmented generation (RAG) pipelines that integrate enterprise data sources and vector databases to deliver impactful business outcomes
• Working cross-functionally with Engineering, Product Management, and customer-facing teams, this individual translates business and customer requirements into production-ready AI solutions
• Key responsibilities include designing and maintaining high-quality data pipelines, performing data preprocessing and model experimentation, and deploying AI/ML services through APIs, microservices, and cloud-native platforms
• The role also focuses on system reliability, model evaluation, and continuous improvement
• This includes developing quantitative and qualitative frameworks to assess model performance and LLM outputs, monitoring scalability and robustness of AI systems, proactively addressing technical risks and customer challenges, and contributing well-documented, modular, and maintainable AI/ML and data engineering solutions
• Success in this role requires a commitment to operational excellence, innovation, and the ongoing advancement of AI capabilities across the organization
• Build, evaluate, and deploy machine learning, deep learning, NLP, and LLM-based applications
• Develop LLM-powered agents and agentic AI systems
• Design prompt engineering strategies and LLM evaluation pipelines
• Implement retrieval-augmented generation (RAG) systems using vector databases and knowledge sources
• Design and maintain scalable, reliable data pipelines and datasets
• Perform data preprocessing, feature engineering, and model experimentation
• Deploy AI/ML services via APIs, microservices, and cloud infrastructure
• Monitor model performance and continuously improve system reliability and scalability
• Collaborate cross-functionally to translate customer needs into technical solutions
• Identify risks, manage customer pain points, and drive continuous improvement initiatives