Expert Team Lead, SWE

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Expert Team Lead, SWE based in Saudi Arabia. This is a hands-on leadership opportunity focused on building and maintaining high-quality human-generated data that supports advanced AI model development. You will lead a team of AI Tutors while remaining directly involved in reviewing, evaluating, and improving technical work. The role combines people leadership, data quality, operational excellence, and software engineering expertise. You will establish quality standards, monitor performance, identify bottlenecks, and introduce scalable improvements. Working closely with data and engineering stakeholders, you will translate evolving model requirements into effective data and evaluation strategies. The environment is fast-paced, collaborative, highly autonomous, and designed for people who thrive on challenging technical problems and continuous improvement. Accountabilities • Own end-to-end quality and delivery for assigned human data projects, personally reviewing technical work and ensuring accuracy, consistency, guideline adherence, and reliable data production at scale. • Lead, coach, and performance-manage a team of AI Tutors, including conducting performance reviews, maintaining development records, creating improvement plans, facilitating shadow sessions, and supporting ongoing professional development. • Participate directly in labeling, annotation, evaluation, and review activities to maintain high standards and demonstrate best practices. • Establish and enforce quality assurance processes, taxonomy standards, workflow guidelines, and evaluation criteria. • Monitor operational KPIs such as quality scores, throughput, and send-back rates, using performance data to identify bottlenecks and improve team efficiency. • Develop and maintain training materials, practice exercises, and certification benchmarks while managing certification processes and workforce adjustments. • Partner with data managers, other team leads, and engineering stakeholders to translate AI model requirements into clear labeling strategies and operational processes. • Foster a high-performance culture through effective coaching, accountability, talent development, and appropriate performance-management actions. • Document project outcomes, identify opportunities for process iteration, and communicate project status, risks, and results to relevant stakeholders. • Represent the needs and perspectives of the AI Tutor team while promoting strong collaboration across the wider human data organization. Requirements • 1+ years of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a comparable operational discipline. • Professional experience building or contributing to scalable, high-performance technology applications, particularly in software engineering or another technical environment. • Demonstrated understanding of data quality metrics, annotation workflows, guideline-driven processes, and quality assurance practices. • Basic knowledge of artificial intelligence and machine learning concepts, including how high-quality training and evaluation data influences model performance. • Experience with people management, coaching, training-program development, performance management, or certification frameworks. • Previous experience leading small teams in data labeling, annotation, technical operations, or related environments is strongly preferred. • Ability to manage multiple projects simultaneously, prioritize effectively, and operate successfully in a fast-moving environment. • Strong analytical capabilities and familiarity with KPI-driven operational improvement; SQL experience is a plus. • Experience working with distributed teams or mixed employment models, including full-time employees and contractors, is advantageous. • Excellent written and verbal communication skills, with the ability to explain complex information clearly, build rapport, and align diverse stakeholders. • Strong organizational skills, meticulous attention to detail, proactive problem-solving abilities, and a continuous-improvement mindset. • Ability to combine strategic thinking with hands-on execution and a willingness to remain directly involved in technical and operational work. • Strong expertise in at least one relevant technical or specialist domain, such as finance, STEM, coding/software engineering, or another technical field. • Passion for developing high-performing teams and scaling reliable, high-quality human data operations. • Candidates must be based in an eligible country supported by the organization, with India among the available locations; remote arrangements may also be possible depending on role and location requirements. Benefits • Competitive compensation, with international compensation details shared during the recruitment process. • Equity participation as part of the broader total rewards package, where applicable. • Comprehensive medical, dental, and vision coverage for eligible employees. • Retirement benefits, including access to a 401(k) plan for eligible U.S.-based positions. • Short- and long-term disability insurance and life insurance for eligible employees. • Paid sick leave and other applicable leave benefits, depending on location and employment type. • Additional employee discounts, perks, and benefits that may vary by jurisdiction and employment arrangement. • Flexible remote-work opportunities where supported by the role and local requirements. • An intellectually challenging environment focused on advanced AI, technical excellence, and continuous learning. • The opportunity to lead and develop a high-performing team while contributing directly to the quality and scalability of AI training and evaluation systems. • Specific compensation, benefits, and employment details will be confirmed during the recruitment process based on location, employment type, experience, and applicable regulations. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment.

1+ years of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a comparable operational discipline. Professional experience building or contributing to scalable, high-performance technology applications, particularly in software engineering or another technical environment. Demonstrated understanding of data quality metrics, annotation workflows, guideline-driven processes, and quality assurance practices. Basic knowledge of artificial intelligence and machine learning concepts, including how high-quality training and evaluation data influences model performance. Experience with people management, coaching, training-program development, performance management, or certification frameworks. Previous experience leading small teams in data labeling, annotation, technical operations, or related environments is strongly preferred. Ability to manage multiple projects simultaneously, prioritize effectively, and operate successfully in a fast-moving environment. Strong analytical capabilities and familiarity with KPI-driven operational improvement; SQL experience is a plus. Experience working with distributed teams or mixed employment models, including full-time employees and contractors, is advantageous. Excellent written and verbal communication skills, with the ability to explain complex information clearly, build rapport, and align diverse stakeholders. Strong organizational skills, meticulous attention to detail, proactive problem-solving abilities, and a continuous-improvement mindset. Ability to combine strategic thinking with hands-on execution and a willingness to remain directly involved in technical and operational work. Strong expertise in at least one relevant technical or specialist domain, such as finance, STEM, coding/software engineering, or another technical field. Passion for developing high-performing teams and scaling reliable, high-quality human data operations. Candidates must be based in an eligible country supported by the organization, with India among the available locations; remote arrangements may also be possible depending on role and location requirements.

Own end-to-end quality and delivery for assigned human data projects, personally reviewing technical work and ensuring accuracy, consistency, guideline adherence, and reliable data production at scale. Lead, coach, and performance-manage a team of AI Tutors, including conducting performance reviews, maintaining development records, creating improvement plans, facilitating shadow sessions, and supporting ongoing professional development. Participate directly in labeling, annotation, evaluation, and review activities to maintain high standards and demonstrate best practices. Establish and enforce quality assurance processes, taxonomy standards, workflow guidelines, and evaluation criteria. Monitor operational KPIs such as quality scores, throughput, and send-back rates, using performance data to identify bottlenecks and improve team efficiency. Develop and maintain training materials, practice exercises, and certification benchmarks while managing certification processes and workforce adjustments. Partner with data managers, other team leads, and engineering stakeholders to translate AI model requirements into clear labeling strategies and operational processes. Foster a high-performance culture through effective coaching, accountability, talent development, and appropriate performance-management actions. Document project outcomes, identify opportunities for process iteration, and communicate project status, risks, and results to relevant stakeholders. Represent the needs and perspectives of the AI Tutor team while promoting strong collaboration across the wider human data organization.