Genai Architect - Banking And Financial Services

The Gen AI Architect will lead the design and implementation of advanced AI, Machine Learning, and Generative AI solutions. This role requires deep hands-on expertise across NLP, computer vision, recommender systems, and MLOps, along with strong architectural leadership to build scalable enterprise-grade AI solutions. Key Responsibilities Architect and deliver end-to-end data-driven solutions using statistical techniques, machine learning, deep learning, and MLOps frameworks. Lead and guide teams in developing AI/ML models across supervised, unsupervised, and deep learning algorithms. Own the MLOps lifecycle including model validation, explainability, monitoring, retraining, and governance (AI Glass Box). Develop solutions across: NLP : Latent semantic analysis, document similarity, document classification, text analytics, language models. Recommender Systems : Content-based and collaborative filtering models. Computer Vision : Neural networks, CNNs, RNNs, and advanced image analytics. Perform statistical modeling and predictive analytics to support business insights. Conceptualize, design, and implement Generative AI (GenAI) solutions— mandatory skill . Engage with stakeholders to translate business problems into scalable AI architectures and roadmaps. Experience Requirements 10+ years of experience in AI/ML model development and deployment , with strong expertise in deep‑dive analytics. 3+ years of experience as a Solution Architect . Technical Skills Programming & Frameworks: Python, Keras/TensorFlow, NLTK Big Data & Distributed Computing: PySpark, Hive Databases: SQL Strong knowledge of machine learning pipeline automation and MLOps best practices.evOps practices, and agile delivery frameworks. • Familiarity with banking domain systems, regulatory considerations, and risk frameworks. • Strong communication and stakeholder management skills, with the ability to influence across tech and business teams.