AI Solution Architect (R-19393)

About the Role

At Dun & Bradstreet data is not just an assetit is the context layer that powers intelligent decision-making. As our AI Solution Architect in Hong Kong you will be a Forward Deployed Engineer who sit at the intersection of D&Bs global data network cutting-edge AI infrastructure and the real-world systems of largest enterprises.

This is not a back-office engineering role. You and your team will be embedded with clientsfrom multinational banks and Fortune 500 manufacturers to cross-border trade platformsto architect deploy and operationalize AI solutions that integrate D&Bs proprietary commercial data directly into their ERP CRM SCM and risk management systems.

You will operate in one of the worlds most regulated financial centers solving high-stakes problems where data privacy cross-border compliance and real-time business intelligence converge.

What Youll Do

Own End-to-End AI Deployment

Scope architect and deliver production-grade AI solutions (RAG pipelines Agent workflows predictive analytics) using D&B data assets and client infrastructure.

Operate in 612 week timeboxes moving from ambiguous business requirements to working prototypes that demonstrate measurable ROI.

Be the Technical-Strategic Bridge

Serve as the senior technical counterpart to C-suite VP and Head of Data stakeholders at client organizations.

Translate complex engineering trade-offs into CFO- and CIO-ready business casescovering revenue impact cost reduction and risk mitigation.

Ensure Enterprise-Grade Compliance

Guarantee all deployments meet SOC 2 ISO 27001 and regional regulatory standards including China PIPL Hong Kong PDPO and financial services sector requirements.

Navigate cross-border data governance with rigorD&Bs credibility depends on it.

Drive Product-Market Feedback Loops

Channel live client insights back to D&Bs Product and AI Labs teams to refine our data APIs model performance and vertical-specific solutions.

Who You Are

Engineering Depth

7 years of product-grade software engineering experience (Python SQL Java/Go preferred).

Proven expertise in cloud infrastructure (AWS/Azure/GCP) data pipelines (Airflow Spark) and enterprise system integration (SAP Salesforce Snowflake etc.).

Hands-on experience with the modern GenAI stack: LLMs vector databases retrieval architecture fine-tuning (LoRA) and Agent frameworks (LangChain LangGraph DSPy).

Client-Facing Leadership

3 years in consulting solutions engineering or client-embedded technical roles.

A track record of delivering AI/ML projects in production within regulated industries (financial services credit risk supply chain or trade finance highly preferred).

Demonstrated ability to manage stakeholder complexity and navigate organizational politics to ship outcomeswhat we call High Agency.

Strategic & Commercial Acumen

Comfortable discussing P&L impact data monetization strategy and competitive positioning with senior executives.

Experience building and scaling technical teams in a high-growth or transformation environment.

Language & Compliance

Business fluency in English and Mandarin (written and spoken). Cantonese is a strong plus.

Working knowledge of data privacy security frameworks (SOC 2 FedRAMP HIPAA) and APAC regulatory landscapes.

Nice-to-Have

Prior experience at top-tier consulting firms or AI-native enterprises with embedded deployment models.

Deep domain expertise in commercial credit data supply chain risk KYB/KYC workflows or trade intelligence.

Published work conference speaking or open-source contributions in applied AI or data engineering.