Director/Sr.Director of AI Engineering

Roles & Responsibilities: Define and drive the long-term AI engineering strategy and roadmap aligned with the company s business goals and innovation vision, focusing on scalable AI and machine learning solutions including Generative AI. Lead, mentor, and grow a high-performing AI engineering team, fostering a culture of innovation, collaboration, and technical excellence. Collaborate closely with product, data science, infrastructure, and business teams to identify AI use cases, design end-to-end AI solutions, and integrate them seamlessly into products and platforms. Oversee the architecture, development, deployment, and continuous improvement of AI/ML models and systems, ensuring scalability, robustness, and real-time performance. Own the full AI/ML lifecycle including data strategy, model development, validation, deployment, monitoring, and retraining pipelines. Evaluate and incorporate state-of-the-art AI technologies, frameworks, and external AI services (e.g., APIs, pre-trained models) to accelerate delivery and enhance capabilities. Establish and enforce engineering standards, best practices, and observability tools (e.g., MLflow, Langsmith) 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 abreast of 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. Bachelor s, Master s, or PhD degree from a top-tier college in Computer Science, Statistics, Mathematics, or related quantitative fields is strongly preferred. Proven experience leading AI engineering teams and delivering production-grade AI/ML systems at scale. Strong expertise in machine learning algorithms, deep learning, NLP, computer vision, and Generative AI technologies. Hands-on experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, Keras, Hugging Face Transformers, LangChain, MLflow, and related tools. Solid understanding of data engineering concepts, ETL pipelines, and working knowledge of distributed computing frameworks (Spark, Hadoop). Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker). Familiarity with software engineering best practices including CI/CD, version control (Git), and microservices architecture. Strong problem-solving skills with a product-oriented mindset and ability to translate business needs into technical solutions. Excellent communication skills to collaborate effectively across technical and non-technical teams. Experience in AI governance, model monitoring, and compliance with data privacy/security standards. Preferred Qualifications: Experience building or managing ML platforms or MLOps pipelines. Knowledge of NoSQL databases (MongoDB, Cassandra) and real-time data processing. Prior exposure to AI in specific domains like banking, finance and credit experience is a strong plus. This role offers the opportunity to lead AI innovation at scale, shaping the future of AI-powered products and services in a fast-growing, technology-driven environment.