Role Overview KPIT is seeking a highly skilled, hands-on Senior Data Scientist / AI Engineer (Remote) to architect, develop, and deliver end-to-end Machine Learning and AI solutions within the Azure ecosystem. The successful candidate will be responsible for the entire AI lifecycle—from designing scalable data pipelines to deploying production-grade AI agents capable of complex, multi-step reasoning. This role is ideal for an engineer who excels at bridging the gap between experimental data science and robust, scalable MLOps. Key Responsibilities End-to-End Solution Delivery: Own the full lifecycle of AI/ML solutions, from initial problem definition and data acquisition to production deployment and monitoring. Data Engineering & Pipeline Development: Build and maintain high-performance, scalable data pipelines using PySpark and Spark on Azure Databricks. Model Development & Feature Engineering: Perform advanced feature engineering, data preparation, and sophisticated model development for diverse business use cases. Agentic AI & GenAI: Develop and deploy AI agents and workflows utilizing multi-step reasoning, tool usage, and Generative AI frameworks. MLOps & Lifecycle Management: Implement and manage MLflow for experiment tracking;
monitor model performance, data drift, and system reliability in production environments. Cross-Functional Collaboration: Partner with Business, Data Engineering, and Analytics teams to translate business requirements into technical AI solutions. Technical Leadership: Act as a subject matter expert, mentoring junior team members and driving engineering best practices. Required Skills & Qualifications Programming & Data: Expert-level proficiency in Python and SQL. Big Data & Cloud: Strong hands-on experience with PySpark, Apache Spark, and Azure Databricks.