Remote Expert Team Lead, AI Data Engineering

Lever, Inc.; Portugal; Híbrido; EUR 70 000 - 150 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Equity opportunities

Comprehensive medical/dental/vision

Resumo da oferta

Lever, Inc. is seeking an Expert Team Lead, Engineering in Portugal to head a team producing high-quality training data for AI models.

You will combine engineering leadership with hands-on review of technical work, and establish standards for accuracy, quality, and guideline adherence. You will coach AI Tutors, manage performance, and develop training and certification programs while collaborating with Human Data and Engineering teams to translate requirements into clear workflows.

Qualificações

• Bachelor's degree or higher in an engineering discipline.
• At least 2 years of professional engineering experience in design, analysis, testing, R&D, or systems integration; or a Master’s degree or higher.
• Basic understanding of AI/ML concepts and the role of high-quality training data.
• Advanced engineering degree such as MS or PhD, or credentials such as PE or FE/EIT, preferred.
• Experience with data-quality metrics, annotation processes, and guideline-driven workflows.
• Breadth across multiple engineering disciplines and ability to review technical work beyond primary specialty.
• Experience with performance management, coaching, training program development, or certification frameworks.
• At least 1 year of hands-on data labeling, annotation, AI training or evaluation, content quality, or similar.
• Experience developing scalable, high-performance technology applications is advantageous.
• Experience leading small teams in data labeling or related environments preferred.
• Proven ability to manage multiple projects, prioritize, and deliver in a fast-paced environment.
• Strong analytical capabilities and experience using data and KPIs to drive continuous improvement; SQL knowledge is a plus.
• Experience managing distributed teams or mixed employment structures.
• Excellent written and verbal communication skills.
• Strong organizational skills and proactive problem-solving mindset.
• Ability to combine strategic thinking with hands-on execution.
• Strong domain expertise in Finance, STEM, Coding/Software Engineering, or another technical field.
• Passion for developing high-performing teams and scaling high-quality human data operations.

Responsabilidades

• Own end-to-end quality and delivery for assigned Human Data projects, reviewing engineering-domain work for accuracy and guideline adherence.
• Lead, coach, and performance-manage a team of AI Tutors (full-time and contractors) through regular reviews and improvement initiatives.
• Oversee labeling and review activities to maintain high standards and effective working practices.
• Ensure adherence to project guidelines, taxonomies, and quality assurance processes.
• Identify bottlenecks and implement process improvements to increase efficiency, quality, and throughput.
• Monitor performance via KPI dashboards (quality, throughput, send-back rates) to guide improvements.
• Create, maintain, and deliver training materials and certification benchmark tasks.
• Manage certification processes and workforce adjustments based on performance and project needs.
• Collaborate with Human Data Managers and Engineering to translate model requirements into labeling strategies.
• Coach and develop team members while maintaining accountability and a high-performance culture.

Conhecimentos

Data quality metrics

Annotation processes

Performance management

Coaching

Project management

SQL knowledge

Formação académica

Bachelor's degree in engineering

Master's degree or higher

PE or FE/EIT

Descrição da oferta de emprego

Lever, Inc. is seeking an Expert Team Lead, Engineering in Portugal to head a team producing high-quality training data for AI models.

You will combine engineering leadership with hands-on review of technical work, and establish standards for accuracy, quality, and guideline adherence. You will coach AI Tutors, manage performance, and develop training and certification programs while collaborating with Human Data and Engineering teams to translate requirements into clear workflows.