Director - AI

About Credit Saison India: Credit Saison India, established in 2019, is one of the fastest-growing Non-Bank Financial Company (NBFC) lenders in the country. With verticals in wholesale, direct lending, and tech-enabled partnerships with NBFCs and fintechs, Credit Saison India's tech-enabled model, along with underwriting capability, facilitates lending at scale, addressing India's significant credit gap, especially within underserved segments of the population. Committed to long-term growth as a lender in India, Credit Saison India serves MSMEs, households, individuals, and more. Registered with the Reserve Bank of India (RBI) and holding an AAA rating from CRISIL and CARE Ratings, the company has a branch network of 45 physical offices, 1.2 million active loans, an AUM exceeding US$1.5B, and an employee base of around 1,000 people. As part of Saison International, a global financial company, Credit Saison India aims to bring people, partners, and technology together to create resilient and innovative financial solutions for positive impact. With operations spanning across various countries, including Singapore, India, Indonesia, Thailand, Vietnam, Mexico, and Brazil, Credit Saison India is dedicated to transforming opportunities and enabling people's dreams. Roles & Responsibilities: Define and drive the long-term AI engineering strategy aligned with the company's business goals, focusing on scalable AI and machine learning solutions, including Generative AI. Lead, mentor, and develop a high-performing AI engineering team, fostering innovation, collaboration, and technical excellence. Collaborate with product, data science, infrastructure, and business teams to identify AI use cases, design end-to-end solutions, and seamlessly integrate them into products and platforms. Oversee the development, deployment, and continuous improvement of AI/ML models and systems to ensure scalability, robustness, and real-time performance. Manage the full AI/ML lifecycle, including data strategy, model development, validation, deployment, monitoring, and retraining pipelines. Evaluate and incorporate cutting-edge AI technologies, frameworks, and external AI services to enhance capabilities and accelerate delivery. Establish and enforce engineering standards, best practices, and observability tools for model governance, performance tracking, and compliance with data privacy and security requirements. Collaborate with infrastructure and DevOps teams to design and maintain cloud infrastructure optimized for AI workloads, including GPU acceleration and MLOps automation. Manage project timelines, resource allocation, and cross-team coordination to ensure timely delivery of AI initiatives. Stay updated on emerging AI trends, research, and tools to continuously evolve the AI engineering function. Required Skills & Qualifications: 10 to 15 years of experience in AI, machine learning, or data engineering roles, with at least 8 years in leadership or managerial positions. Bachelors, Masters, or PhD degree in Computer Science, Statistics, Mathematics, or related fields from a top-tier college is preferred. Proven track record of leading AI engineering teams and delivering production-grade AI/ML systems at scale. Expertise in machine learning algorithms, deep learning, NLP, computer vision, and Generative AI technologies. Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, Hugging Face Transformers, LangChain, MLflow, and related tools. Strong understanding of data engineering concepts, ETL pipelines, and distributed computing frameworks like Spark and Hadoop. Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker). Familiarity with software engineering practices, CI/CD, version control (Git), and microservices architecture. Strong problem-solving skills with a product-oriented mindset and the ability to translate business requirements into technical solutions. Excellent communication skills for effective collaboration across technical and non-technical teams. Experience in AI governance, model monitoring, and compliance with data privacy/security standards. Preferred Qualifications: Experience in building or managing ML platforms or MLOps pipelines. Knowledge of NoSQL databases (MongoDB, Cassandra) and real-time data processing. Previous exposure to AI in domains like banking, finance, and credit is advantageous. This role presents an opportunity to lead AI innovation at scale, shaping the future of AI-powered products and services in a rapidly growing, technology-centric environment.,