AI Architect
Location: UnionBank Plaza, Ortigas, Pasig City
Employment Type: Full-time
About The Role
The AI Architect supports the definition and implementation of enterprise AI/ML/Generative AI architectures, ensuring solutions are scalable, secure, and responsible. Working within the Data & AI Architecture group, the role contributes to integrating AI/GenAI capabilities into strategic platforms, data products, and enterprise systems, while collaborating closely with data architecture as the enterprise AI architecture framework continues to mature. This position partners with business, technology, data engineering, governance, and risk teams to deliver practical architecture guidance that accelerates value delivery while upholding reliability, compliance, and ethical standards.
What You'll Do:
AI Architecture
- Contribute to the enterprise AI/ML/GenAI architecture blueprint by developing and documenting solution patterns across model pipelines, MLOps/LLMOps, data flows, and system integrations.
- Support evaluation and adoption of AI/ML/GenAI technologies, frameworks, and platforms (cloud and on-prem), aligned with enterprise standards and delivery feasibility.
- Support architecture reviews and technical councils by preparing design artefacts and ensuring solutions align with enterprise architecture principles, security standards, data governance requirements, and responsible AI controls.
- Support the integration of AI solutioning into enterprise delivery and AICoE/DSAG processes to ensure timely data and AI architectural input from early design through execution.
Solution Design & Delivery
- Design AI/ML/GenAI solution architectures across the model lifecycle - from data sourcing to deployment and monitoring - aligned with enterprise standards.
- Apply reusable AI patterns and components (e.g., feature stores, vector databases, LLM/agent integration, and model serving) to promote consistency and delivery speed.
- Provide architecture support to resolve issues across performance, data dependencies, data quality impacts on AI outcomes, and model lifecycle management.
- Deliver assigned architecture outputs on scope, quality, and agreed timelines/SLAs, escalating risks and dependencies as needed.
- Contribute to data architecture solutioning where required as part of the group's ongoing data and AI transformation.
- Perform proof-of-concept and/or proof-of-value activities and well as drive pilot projects of emerging AI (with data) platforms and technologies to accelerate adoption by the business teams.
Governance, Risk, & Compliance
- Apply responsible AI standards and guardrails across the model lifecycle, including documentation and explainability requirements.
- Work with Model Risk, Cybersecurity, and Data Governance teams to ensure AI solutions meet regulatory requirements, internal controls, and enterprise risk frameworks.
- Support adherence to enterprise AI/ML governance frameworks through design guidance, evidence preparation, and review follow-through.
Stakeholder & Cross-Functional Collaboration
- Work with business units and delivery teams to translate AI/GenAI needs into solution architectures and roadmap inputs, coordinating with data architecture during the group's transformation.
- Collaborate with Engineering, Cloud, Security, and Data teams to integrate AI solutions into enterprise platforms and data products.
- Participate in Architecture Review Boards and technical councils, providing AI/ML architecture inputs and supporting cross-domain decisions.
Professional Development
- Contribute to knowledge sharing by documenting patterns, lessons learned, and reusable assets across AI and data architecture domains.
- Continuously upskill in AI/ML/GenAI technologies, responsible AI practices, and enterprise architecture standards.
What We're Looking For:
- Bachelor's degree in a relevant field; cloud/AI certifications are a plus.
- 2+ years in solution or architecture roles (or equivalent experience); experience in regulated industries preferred.
- Working knowledge of AI/ML and LLM concepts, MLOps/LLMOps fundamentals, cloud platforms, and responsible AI practices.
- Strong communication, analytical, and documentation skills.
- Experience with enterprise data and AI platforms and modern GenAI architectures (including agentic patterns) is preferred.
- High-quality AI architecture designs delivered on time and aligned with enterprise standards.
- Increased reuse of approved AI patterns and components across initiatives.
- Strong compliance with responsible AI, security, and governance requirements.
- Positive stakeholder feedback on architecture support and collaboration.
