AI Builder

About the role

As an AI Builder, a full-stack AI software engineer, you will drive the engine of core AI innovation, acting as a visionary who leverages cutting-edge artificial intelligence tools and New Ways of Working (NWoW) methodologies to design and deliver high-quality solutions at unprecedented speed. You will operate at the critical intersection of executive strategy and technical execution, balancing rapid delivery and organizational momentum with technical excellence, security, and long-term maintainability. You will guide a team of talented engineers to transform theoretical explorations into practical, production-grade solutions, fostering a high-performance culture that uses AI-powered development tools and automated testing to redefine market leadership.

Key responsibilities

• Process analysis and optimization. Together with the Process Owner (PO), analyze the current process, and identify challenges and opportunities to improve to deliver tangible results towards the business goals. Translate business requirements into user stories, technical specifications, blueprints, and documentation by leveraging AI tools for maximum efficiency.
• Architect and govern scalable, secure, and maintainable enterprise AI solutions using AI-assisted architecture patterns and frameworks.
• Facilitate and govern business readiness by coordinating with the project team, and ensures all requirements in the Business Readiness Checklist are considered, and typically sets up BRC kickoff/closure sessions and walks through BR items with the squad.
• Create and manage agile artifact and structure documentation: Responsible for producing and centralizing project documentation, including Solution Design Documents (SDD) and Solution Architecture document, API specifications, git commit documentations, and operational runbooks, ensuring all project knowledge is captured for long-term sustainability.
• Lead solution development using AI-powered IDEs (e.g., Cursor, GitHub Copilot), advanced code generation tools, and automated development assistants to accelerate delivery without compromising quality.
• System integration & interoperability. Responsible for applying and/or integrating AI models into existing systems (e.g., core wallet, CRM, SAP, and others). Design and develop robust APIs and middleware layers that ensure seamless data flow and functional interoperability between AI agents and legacy infrastructure.
• Drive the horizontal application of AI models across different business units, ensuring that a single model or framework can be leveraged to enhance multiple core functions, from customer-facing interfaces to back-end settlement systems.
• Operationalize AI models into production systems by collaborating closely with data science and machine learning teams to collaborate with AI Scientists and collaborate in applying AI model tuning, and experimental validation, and ensure model integration, robust deployment, and full production readiness.
• Adhere to Security by Design. Secure the AI lifecycle against emerging threats, such as prompt injection, data poisoning, and model inversion, by integrating automated security scanning and vulnerability assessments. In addition, design and implement AI solutions ensuring robust encryption of PII data and compliance with global data protection standards (e.g., PH Data Privacy Act, GDPR, etc).
• Drive agile delivery through iterative sprints, rapid prototyping, and continuous feedback loops to accelerate learning. Establish optimized CI/CD pipelines and DevOps practices specifically tailored for AI-accelerated development and monitoring.

About you

• 6+ years of experience in software development and solution architecture, with at least 3 years hands-on in building Machine Learning (ML) models.
• 1+ years of hands-on experience specifically with AI-powered development tools such as Cursor, GitHub Copilot, Tabnine, or Amazon CodeWhisperer.
• Deep proficiency in modern programming languages (Python, Java, TypeScript, or Go) and cloud platforms (AWS, Azure, or GCP).
• Strong knowledge of microservices, APIs, containerization (Docker, Kubernetes), and event-driven systems.
• Proven track record implementing Agile/Scrum, DevOps, and familiar with MLOps principles.
• Advanced understanding of LLM integration, prompt engineering, and automated validation frameworks.
• Ability to thrive in rapidly evolving, AI-driven environments with a creative and systematic approach to problem-solving.
• Excellent communication skills, capable of translating complex concepts for both technical teams and non-technical management.
• Master's degree in Computer Science, Information Technology, AI, or a related technical field (preferred).
• Background in banking, fintech, or other highly regulated industries (preferred).