AI Platforms Lead

Job Title: AI Platforms Lead

Office Location: UnionBank Plaza - Ortigas, Pasig City

Employment Type: Probationary

About The Role

The AI Platforms Lead defines, shapes, and shepherds the platforms that power the bank's AI capabilities. As capabilities such as Knowledge Assist, SDLC Assistant, IDP, Agentic builder, and future GenAI products move from incubation toward production, this role ensures each one rests on a deliberately chosen, well-architected platform foundation — defining requirements, evaluating vendors, designing reference architectures, and feeding those architectures into the Data & AI Architecture team for enterprise consistency.

This is a hands-on technical leadership role. The right person is comfortable moving between vendor negotiations, architectural whiteboards, executive narratives, and engineering deep-dives — often in the same week. They serve as the AI CoE's principal technical voice on platform decisions and act as a trusted thinking partner to the Head of AI CoE on portfolio strategy, vendor positioning, and executive communication.

What You'll Do

Platform Definition & Vendor Engagement

• Define platform requirements for each AI capability the CoE incubates, translating business and technical needs into clear specifications that guide build-vs-buy decisions.
• Lead vendor evaluation and engagement across the GenAI platform landscape — model providers, orchestration frameworks, RAG infrastructure, evaluation tooling, observability — ensuring selected platforms meet the bank's needs for scale, security, regulatory posture, and total cost of ownership.
• Negotiate and shape vendor relationships as the CoE's technical principal — challenging roadmaps, surfacing trade-offs, and ensuring the bank is not led into vendor-driven decisions misaligned with strategy.
• Maintain a forward view of the platform landscape so platform choices made today remain defensible 18–24 months out as the GenAI ecosystem evolves.
  
  

Reference Architecture & Technical Leadership

• Design reference architectures for each AI platform the CoE adopts, capturing integration patterns, data flows, security boundaries, and operational expectations.
• Feed reference architectures to the Data & AI Architecture team as inputs to enterprise architecture standards
• Provide design review and technical guidance to capability delivery teams within the CoE, ensuring platform choices are applied consistently across capabilities.
• Own technical coherence across the CoE's platform portfolio — preventing fragmentation, duplication, and accidental incompatibility across capabilities that share underlying infrastructure.
  
  

Capability & Platform Lifecycle

• Identify when a capability requires a dedicated platform owner as it matures, and shape the transition plan from CoE-incubated platform to a stable, owned, operational platform.
• Define platform success criteria and graduation thresholds — the conditions under which a platform is ready to be handed off to a long-term owner outside the CoE.
  
  

Strategic Advisory & Executive Engagement

• Serve as principal technical advisor to the Head of AI CoE on platform strategy, vendor positioning, build-vs-buy decisions, and architectural direction.
• Develop executive-grade narratives for Execom and board-level audiences on the bank's AI platform posture, vendor landscape, and emerging capability needs.
• Support portfolio prioritization by surfacing platform-level dependencies, sequencing constraints, and reuse opportunities across capabilities.
  
  

What We're Looking For

• 10+ years of progressive experience in AI/ML, software, or platform engineering, with at least 3 years in technical leadership roles.
• Demonstrated experience designing or operating AI/ML platforms in production environments — including familiarity with LLM serving, RAG infrastructure, agent frameworks, and AI observability tooling.
• Strong architectural skills: able to design reference architectures, document them clearly, and defend trade-offs to senior technical and non-technical audiences.
• Experience leading vendor evaluation and engagement at enterprise scale — comfortable in commercial negotiation, technical due diligence, and roadmap influence.
• Ability to operate in regulated environments: familiarity with banking, financial services, or comparable regulatory expectations on data, security, and AI risk.
• Excellent communication skills, with proven ability to translate technical depth into executive-grade narrative.
• Track record of partnering effectively with adjacent architecture and platform functions, contributing to shared standards rather than competing for ownership.
• Hands-on experience with at least one major GenAI platform stack (e.g. Azure OpenAI, AWS Bedrock, Vertex AI, or comparable) and one orchestration / agent framework.
• Prior experience in a Center of Excellence, platform engineering function, or principal engineer role within a large enterprise.
• Exposure to AI governance, responsible AI design, and AI-specific security patterns (prompt injection, data leakage, model abuse).
• Comfort serving as a thinking partner to senior leaders on strategy, prioritization, and organizational direction.