Gen AI Solution Architect

Gen AI Solution Architect

Key Responsibilities

• Architect end-to-end AI/ML solutions using Python, TensorFlow, PyTorch, and scikit-learn, ensuring robust model development and deployment frameworks.
• Design scalable data pipelines and real-time processing systems utilizing Apache Spark, Kafka, and PostgreSQL to support machine learning workflows.
• Guide the team in implementing advanced ML models, including deep learning, NLP, and time series forecasting, using tools such as XGBoost, LightGBM, and Spark MLlib.
• Oversee integration of data engineering platforms like Apache Airflow, DataBricks, and RabbitMQ to optimize data ingestion, transformation, and orchestration for AI/ML projects.
• Ensure technical excellence by advocating best practices in model validation, performance optimization, and reproducibility across Python, R, and SQL-based environments.
• Collaborate with stakeholders to gather requirements, translate business needs into technical specifications, and deliver tailored AI/ML solutions that meet quality and compliance standards.
• Mentor and coach team members in advanced AI/ML concepts, fostering continuous learning and adoption of emerging technologies within the skill cluster.
• Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments.

Skill Requirements

• Expert Proficiency In Ai/Ml Model Development, Including Classical Machine Learning, Deep Learning, Nlp, And Time Series Forecasting.
• Excellent Knowledge Of Python, R, Sql, And Bash For Data Analysis, Model