URGENT! AI Architect
Summary
Designs enterprise AI systems using LLMs, RAG, and agent frameworks on cloud platforms like Azure, AWS, or GCP while ensuring governance and safety standards.
Location: BGC, Taguig City | Hybrid (M-F)
Employment type: Full-time | Day Shift
Role Overview
We are seeking an Enterprise AI Solution Architect to lead the end-to-end architecture and solution design for enterprise AI initiatives. In this role, you will bridge business requirements with cloud-native AI engineering—designing resilient LLM architectures, RAG systems, and AI agent frameworks aligned with enterprise governance, safety standards, and architecture best practices.
Key Responsibilities
End-to-End AI Architecture: Lead the design and implementation of production-grade AI solutions across assigned enterprise projects.
Stakeholder Engagement: Partner with business leaders and product teams to translate business needs into technical architectures and measurable success criteria.
Governance & Standards: Assess proposed architectures against enterprise "golden paths" and Community of Practice (CoP) design patterns.
AI Safety & Evaluation: Design robust evaluation frameworks, safety guardrails, and risk mitigation strategies for generative AI and LLM workloads.
Architecture Leadership: Lead architecture review boards, communicate trade-offs to stakeholders, and mentor engineering teams on implementation.
Cross-Functional Collaboration: Align AI Engineers, Cloud Infrastructure Teams, and Platform Lead Engineers to continually refine enterprise AI blueprints.
Key Qualifications
Core Requirements
Professional Experience: 3+ years in software engineering, IT architecture, or cloud solution design.
Enterprise AI & Cloud: 1+ years of hands-on experience designing enterprise cloud architectures across Azure, AWS, or GCP.
AI Stack Mastery: Deep understanding of LLMs, Retrieval-Augmented Generation (RAG), AI Agents, and Model Evaluation techniques.
Cloud AI Ecosystems: Practical experience with cloud AI suites (e.g., Azure OpenAI, Azure Cognitive Services, or AWS/GCP equivalents).
Data & Security Governance: Working knowledge of cloud data governance, enterprise security controls, access models, and compliance standards for AI.
Education: Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline.
RH-TT