AI Engineer

The AI Engineer is responsible for designing, building, and deploying AI and machine learning solutions that enhance Cielo’s products, analytics capabilities, and automation strategy. This role leads the development of scalable AI models, integrates advanced techniques such as LLMs and RAG, and partners across Product, Innovation, Technology, and Data Engineering to support enterprise-wide AI adoption. The AI Engineer provides technical leadership, contributes to AI strategy execution, and ensures that AI solutions are performant, secure, compliant, and aligned with business objectives.

• Design, develop, and deploy Generative AI, Agentic AI, or AI/ML models focused on talent acquisition use cases such as candidate matching, skill assessment, and recruitment forecasting
• Assess the effectiveness and accuracy of AI/ML models through rigorous testing, validation, and performance metrics analysis
• Identify new data sources and features that could enhance the quality and accuracy of AI/ML models to improve predictions and recommendations
• Perform data engineering tasks to source data from internal operational systems, client Applicant Tracking Systems, and 3rd-party vendors through APIs, direct database connections, and data exports
• Apply statistics, machine learning, and advanced analytic approaches to predict and optimize business outcomes in the talent acquisition space
• Build and maintain data pipelines using AWS services to ensure reliable data flow for AI/ML models
• Develop and optimize REST and SOAP APIs for internal and external consumption
• Implement and fine-tune large language models (LLMs) for specific talent acquisition tasks such as resume parsing, job description analysis, and candidate communication
• Create agentic AI systems that can autonomously perform recruitment tasks and assist human recruiters
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
• Document AI/ML models, data pipelines, and system architectures for knowledge sharing and maintenance
• Stay current with emerging AI technologies and methodologies to continuously improve our talent acquisition capabilities
• Work with business partners to translate their processes, rules, and requirements into actionable objectives.
• Apply statistics, machine learning, and advanced analytic approaches to predict and optimize business outcomes.