Ai Engineer

AI Engineer

The AI Engineer is responsible for designing, developing, deploying, and maintaining Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions that drive innovation, operational efficiency, risk management, and customer experience improvements across Popular.

This position serves as a key technical contributor within Popular's AI Office and partners closely with Data & Analytics, Enterprise Architecture, Cybersecurity, Infrastructure, Software Engineering, Risk Management, Compliance, Legal, and business units to deliver secure, scalable, and compliant AI solutions. The AI Engineer is responsible for engineering enterprise-grade AI applications, implementing model lifecycle management practices, and ensuring AI solutions align with Responsible AI principles, regulatory requirements, and technology standards applicable to the financial services industry.

The role combines strong software engineering, data science, cloud architecture, and AI platform expertise to accelerate AI adoption while maintaining the highest levels of governance, security, resiliency, and operational excellence.

Key Responsibilities

AI Solution Engineering & Development

Design, develop, test, deploy, and support AI, Machine Learning, and Generative AI solutions that address strategic business objectives and operational challenges.
Build scalable AI-enabled applications, APIs, intelligent assistants, virtual agents, copilots, and automation solutions.
Develop and maintain reusable AI frameworks, engineering standards, and reference architectures to accelerate enterprise adoption.Translate business requirements into technical AI solution designs that meet functional, security, performance,
and compliance requirements.
Collaborate with business stakeholders, product owners, and technical teams to deliver production-ready AI capabilities.

Generative AI & Intelligent Automation

Design and implement Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, and enterprise knowledge management capabilities.
Develop agentic AI workflows that automate and orchestrate business processes while maintaining appropriate governance and human oversight.
Optimize prompt engineering, model orchestration, grounding strategies, and response quality frameworksEvaluate and integrate emerging AI technologies, platforms, and capabilities that support enterprise innovation objectives.
Support development of internal AI copilots and digital workforce solutions that improve employee productivity and customer experiences.

AI Platform Engineering & MLOps

Develop and support AI engineering platforms, model deployment frameworks, and MLOps capabilities.
Build and maintain CI/CD pipelines, automated testing frameworks, model monitoring, and deployment automation for AI solutions.
Implement observability, logging, telemetry, and performance monitoring across AI applications and services.
Support model lifecycle management, version control, retraining, validation, and operational monitoring.
Ensure AI solutions are scalable, resilient, and aligned with enterprise technology standards.

AI Risk, Governance & Responsible AI

Ensure AI solutions comply with enterprise policies, cybersecurity standards, model risk management requirements, privacy regulations, and applicable financial industry regulations.
Support implementation of Responsible AI practices including fairness, transparency, explainability, accountability, and human oversight.
Participate in AI governance reviews, model validation processes, architecture reviews, and risk assessments.
Maintain technical documentation, model artifacts, deployment records, inventories, and audit evidence required for regulatory and internal oversight.
Collaborate with Risk Management, Compliance, Legal, Information Security, and Internal Audit teams throughout the AI lifecycle.

Innovation & Continuous Improvement

Research emerging AI, machine learning, and cloud technologies to identify opportunities for business value creation.
Participate in proof-of-concepts, pilot initiatives, and innovation programs sponsored by the AI Office.
Provide technical guidance and mentorship to engineering and technology teams regarding AI engineering best practices.
Contributes to the establishment of enterprise AI engineering standards, development methodologies, and operating procedures.

Required Qualifications

Education

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Data Science, Artificial Intelligence, Mathematics, Statistics, or a related technical field.
Master's degree in Artificial Intelligence, Data Science, Computer Science, Engineering, or related discipline preferred.

Experience

5+ years of expe