The Sr. Director of AI Engineering will lead a team of AI and machine learning engineers to build and optimize AI-driven solutions across multiple applications. This role is crucial for driving AI strategy, ensuring scalability and integration of AI models, and fostering a data-driven culture throughout the organization. **Responsibilities:** + Lead the design, development, and deployment of AI/ML solutions, ensuring alignment with business goals. + Collaborate with data scientists, product managers, and engineering teams to integrate AI models into production systems. + Drive architectural decisions for AI infrastructure to support scalability, robustness, and model lifecycle management. + Mentor and manage AI engineering team members, promoting best practices in model training, deployment, and maintenance. + Implement rigorous testing, monitoring, and validation processes for AI models to ensure accuracy and reliability. + Stay updated on industry trends and emerging AI technologies, evaluating and integrating new tools to maintain a cutting-edge tech stack. + Foster a culture of continuous learning and innovation within the team, supporting career development and technical growth. + Oversee the integration of AI solutions with data storage, cloud platforms, and data engineering pipelines to support high-performance applications. + Ensure compliance with data governance, privacy, and security standards in all AI-driven solutions. **Qualifications:** + Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field (Ph.D. preferred). + 15+ years of experience in software or AI engineering with 5+ years in a leadership role managing teams of 15+ engineers. + Strong background in AI/ML model development, deployment, and monitoring using frameworks such as TensorFlow, PyTorch, or Scikit-Learn. + Demonstrated experience of prompting engineering, retrieval-augmented generation, fine-tuning and other advanced AI techniques. + Proficiency with data processing technologies, relational and NoSQL databases, and cloud platforms (e.g., AWS, Azure, GCP). + Experience with MLOps practices, including CI/CD pipelines, model. + versioning, and automated retraining. + Strong communication skills and a proven track record of delivering impactful AI solutions. + Knowledge of agile methodologies and familiarity with project management tools like Jira or Asana. + Experience with data privacy and ethics in AI, including regulatory considerations. **Preferred Skills:** + Familiarity with AI research methodologies and a strong network within the AI research community. + Experience in deep learning architectures, reinforcement learning, or generative AI models. + Proven ability to scale AI teams and implement high-performance AI infrastructure. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.