Principal AI Engineer

The Principal AI Engineer provides technical leadership and direction for a team of AI Engineers, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives. Focus: End-to-End Initiative Leadership, AI/ML Strategy & Mentorship.

The difference you will make

• Provide technical leadership, guidance, and mentorship to a team of AI Engineers.
• Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production.
• Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans.
• Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing.
• Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments.
• Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation.
• Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.
• Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth.
• Act as a primary technical point of contact for stakeholders regarding AI solutions.
• Hands-on contribution to critical code components, architectural design, and complex problem-solving.

What you will bring to the role

Education: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred.

Experience: 8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end.

Technical Skills:

• Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras).
• Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving.
• In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).
• Strong architectural skills for building robust, scalable, and maintainable AI infrastructures. o Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services.
• Excellent understanding of data engineering principles, data governance, and database technologies.
• Ability to evaluate and make sound technical decisions on complex trade-offs.

Soft Skills:

• Strong ownership and accountability for assigned work.
• Clear and professional verbal and written communication.
• Effective time management and task prioritization.
• Analytical thinking and problem-solving skills.
• Ability to work independently, collaborate effectively and mentor junior team members.
• Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
• Adaptability and learning agility in a fast-paced environment.
• Strong attention to detail and a commitment to quality.
• Receptiveness to feedback and continuous improvement mindset.