AI Solution Architect (R-19393)

Shape the Future with Dun & Bradstreet

At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

About the Role

At Dun & Bradstreet, data is not just an asset—it 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&B’s 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 clients—from multinational banks and Fortune 500 manufacturers to cross-border trade platforms—to architect, deploy, and operationalize AI solutions that integrate D&B’s proprietary commercial data directly into their ERP, CRM, SCM, and risk management systems.

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

What You’ll 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 6–12 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 cases—covering 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 rigor—D&B’s credibility depends on it.

Drive Product-Market Feedback Loops

• Channel live client insights back to D&B’s 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 outcomes—what 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.