AI Solution Architect China Hub
Objective of Job\:
Drive the design and implementation of scalable AI and machine learning solutions that address complex business challenges and unlock new value across the organization. Translate business requirements into robust technical architectures, bridging the gap between data science, engineering, and business strategy. Partner with cross-functional stakeholders to evaluate, prototype, and deploy AI capabilities through structured delivery processes (Gate 0–3), ensuring alignment with enterprise architecture standards and long-term technology roadmaps.
Key Responsibilities
AI Architecture & Solution Design
Design end-to-end AI/ML solution architectures covering data pipelines, model training, deployment, and monitoring infrastructure.
Define technical blueprints for scalable, secure, and production-ready AI systems aligned with enterprise architecture standards.
Evaluate and recommend AI/ML frameworks, platforms, and cloud services (Azure, AWS, GCP) based on use-case requirements.
Establish design patterns, reference architectures, and reusable components for AI solutions across the organization.
Use Case Development & Governance
Own the technical scoping of AI use cases from ideation through Gate 0–3 approval, ensuring feasibility and value alignment.
Ensure compliance with data governance, model risk management, and responsible AI principles.
Challenge technical assumptions, identify integration risks, and articulate trade-offs between complexity, cost, and performance.
Support AI steering committees and senior leadership with clear, decision-ready technical assessments.
Data Strategy & MLOps
Collaborate with data engineering, platform, and DevOps teams to design robust data pipelines and feature stores.
Define MLOps strategies covering model versioning, CI/CD for ML, A/B testing, monitoring, and retraining workflows.
Support data quality initiatives and ensure training data integrity across AI workloads.
Technology Evaluation & Innovation
Conduct technology scouting and proof-of-concept development for emerging AI capabilities (LLMs, GenAI, computer vision, NLP).
Benchmark AI solutions against industry standards, competitor approaches, and state-of-the-art research.
Assess build-vs-buy decisions and vendor solutions for AI platforms and tools.
Communication & Stakeholder Management
Translate complex AI concepts into clear, compelling narratives for both technical and non-technical stakeholders.
Prepare executive-ready architecture proposals, roadmaps, and technical documentation to communicate solution strategies.
Act as a trusted technology partner, fostering an AI-first and innovation-driven culture across the organization.