Title: AI Engineering Manager We are seeking an experienced AI Engineering Manager to lead our AI/ML Data Engineering team and collaborate with Cloud, Frontend, Backend, and DevSecOps teams. Key Responsibilities: - Recruit, mentor, and develop a high-performing, diverse AI/ML and Data engineering team—fostering collaboration, continuous learning, and clear performance metrics to drive retention in a fast-paced environment - Champion technical excellence by applying first principles thinking and data-driven problem solving, enforcing rigorous code reviews, automated testing, and comprehensive documentation while promoting Agentic, MLOps, and LLMOps best practices - Implement Agile methodologies to conduct regular gap analyses and risk assessments, transforming process deficiencies into stable processes - Collaborate with the CAIO to define and execute a technical roadmap that balances cutting-edge AI product development with enterprise-grade reliability, security, and performance, while integrating emerging trends - Oversee the entire AI product lifecycle—from proof-of-concept through production deployment, monitoring, and iterative improvement—ensuring alignment with business objectives, client needs, and industry standards - Manage product timelines, resource allocation, and deliverables through effective task management, delegation, and milestone tracking, while maintaining high team morale - Serve as an AI liaison for internal stakeholders, proactively communicating progress, identifying risks, and diffusing tensions through transparent documentation and open dialogue - Embrace a product owner mindset to prioritize tasks and manage the product backlog, aligning technical development with strategic business goals - Drive product evolution by providing insights on scalable architecture, governance, and advanced LLM/Agentic techniques, shaping a forward-thinking AI vision that anticipates future trends - Establish and monitor clear KPIs and performance metrics through regular reviews and retrospectives to ensure accountability and continuous improvement - Foster cross-functional collaboration across Data, AI, Backend, DevSecOps, QA, and Frontend teams via structured communication and transparent reporting, ensuring cohesive alignment across the organization - Cultivate innovation by promoting experimentation, calculated risk-taking, and continuous feedback loops that leverage data analytics to refine models, processes, and products