Lead AI/ML Architect

Job Description:
Need Exceptional exp in AI/ML concepts (GenAI, Agentic, RAG), Vector DB works, news recommendation system using GenAI) or provide details about existing projects like claims processing. metadata extraction

Primary Responsibilities:

AI Project Execution & Delivery:
•           Lead the end-to-end execution of high-priority AI/ML projects, ensuring they are delivered on time, within budget, and to the highest technical standards.
•           Translate the enterprise AI strategy and product roadmaps into detailed project plans, technical specifications, and actionable backlogs for engineering teams.
•           Manage the day-to-day operations of the AI Review Board (AIRB) submission process, acting as a hands-on guide for Data Science and product teams.
•           Facilitate the preparation of all required documentation for AIRB reviews, ensuring submissions are complete, clear, and proactively address potential ethical, compliance, and technical concerns.
•           Implement and enforce the governance framework, ensuring teams adhere to established standards and best practices for responsible AI.
Team Leadership & Technical Mentorship:
•           Provide direct line management, technical leadership, and mentorship to a team of senior AI/ML Engineers and Data Scientists.
•           Drive the practical implementation of the MLOps strategy, directly overseeing the construction and optimization of CI/CD pipelines for AI/ML systems using tools like GitHub Actions.
•           Enforce rigorous engineering hygiene, including version ntrol for code, data, and models (Git, DVC), and the application of Infrastructure as Code (IaC) principles.
•           Lead the technical implementation of production monitoring solutions to track model performance, identify drift, and ensure the long-term reliability of deployed AI systems.

Required Qualifications:
•           Proven AI/ML Leadership: 10-15 years of experience in the AI/ML field, with at least 4-5 years in a leadership or management role leading technical teams in the delivery of complex AI solution
•           Hands-on MLOps Experience: Proven experience building and managing CI/CD pipelines and MLOps workflows for machine learning.
•           Strong Technical Foundation: Proficient in Python, common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and cloud platforms (AWS, Azure, or GCP).