Lead Engineer Artificial Intelligence Role
This pivotal position is responsible for driving the strategic vision and technical execution of AI platforms and MLOps initiatives within the organization. The ideal candidate will possess expertise in Machine Learning, Generative AI, and Large Language Models combined with deep knowledge of model lifecycle operations, observability, and governance.
The Lead Engineer will architect and operationalize scalable AI/ML platforms, ensuring solutions are reliable, reproducible, and compliant with organizational and regulatory requirements. Success in this role requires balancing technical depth with leadership—guiding teams, fostering collaboration, and embedding operational excellence across the enterprise.
Key Responsibilities:
Design and execute AI/ML solutions across the lifecycle, including model training, evaluation, deployment, and monitoring.
Architect and scale CI/CD and Infrastructure-as-Code pipelines for ML and GenAI workloads.
Collaborate closely with data scientists, ML engineers, and software engineers to ensure seamless integration of models and services into production systems.
Requirements:
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Demonstrated expertise in designing and deploying cutting-edge AI solutions that drive measurable business impact.
Demonstrated understanding of ethical considerations in AI systems.
3+ years of project leadership experience including Agile project management.
Preferred Qualifications:
Experience leading enterprise-scale MLOps initiatives.
Deep experience with MLflow or equivalent lifecycle platforms (tracking, registry, deployment).
Expertise in scalable serving patterns (real-time inference, batch/streaming), containerization, and GPU-optimized deployments.
This role offers a unique opportunity to make a significant impact on the organization's AI strategy and contribute to the development of innovative solutions.
As a key member of the team, you will be expected to stay updated on advancements in AI research, MLOps practices, and AI platform technologies to guide initiatives and drive business growth.