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.
