About this role
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. Since 1841, 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.
Key Responsibilities:
- Define the architecture and technical direction for enterprise AI/ML and GenAI capabilities, including agentic and conversational AI solutions using platforms and models such as Vertex AI Agent Builder/ADK and Gemini
- Lead the design and delivery of production-grade LLM applications, including embeddings, RAG pipelines, vector database integration, tool use, orchestration, and multi-agent patterns
- Establish reusable AI engineering standards, reference architectures, design patterns, and governance controls for secure, responsible, observable, and maintainable AI solutions
- Provide technical leadership for end-to-end MLOps and CI/CD capabilities supporting model experimentation, evaluation, validation, deployment, monitoring, and lifecycle management
- Architect and guide scalable cloud-native AI services on GCP and Kubernetes using Docker, Infrastructure as Code such as Terraform, and event-driven integration patterns
- Lead the design of data pipelines, APIs, and enterprise integrations that embed AI/ML capabilities into business applications and collaboration platforms
- Define model and system evaluation approaches for quality, safety, latency, reliability, cost, and business effectiveness; guide production monitoring, incident response, root-cause analysis, and prevention
- Partner with Product Owners, Data Scientists, AI Data Engineers, Platform Architects, Security, Risk and Compliance, and application teams to evaluate trade-offs and deliver cost-effective solutions aligned to enterprise standards
- Lead technical design reviews, proofs of concept, and technology evaluations; influence build-versus-buy decisions and the adoption of emerging AI tools and platforms
- Provide training, guidance, and mentorship to engineers and raise engineering capability through code reviews, architecture reviews, knowledge sharing, and best-practice adoption
- Additional duties as assigned
Key Skills:
- Bachelor’s degree in computer science, Engineering, or a related field; master’s degree preferred
- 12+ years of relevant software engineering experience, including substantial experience architecting and deploying production AI/ML solutions at enterprise scale
- Proven technical leadership in the architecture and delivery of large-scale, distributed AI systems across multiple teams or products
- Deep hands-on expertise with agentic AI frameworks and platforms, including Vertex AI Agent Builder / ADK, and large language models such as Gemini
- Expertise in Python application development and APIs, including frameworks such as FastAPI, with strong software design, testing, code review, and version-control practices
- Proven experience designing LLM-based applications, including RAG pipelines, embeddings, vector databases, tool integration, orchestration, prompt and context engineering, and model evaluation
- Deep experience with GenAI frameworks and ecosystems such as LangChain and Hugging Face
- Proven experience designing end-to-end MLOps capabilities using tools such as Vertex AI Pipelines, MLflow, or Kubeflow
- Advanced experience architecting cloud-native solutions on GCP; experience with AWS AI/ML services is a plus
- Proven experience deploying and operating scalable AI/ML services using Docker, Kubernetes, Terraform, CI/CD, observability, and incident-management practices
- Experience defining AI quality, safety, security, privacy, governance, performance, reliability, and cost-management standards for production systems
- Experience with event-driven workflows, enterprise data pipelines, and integrations such as Microsoft Teams and Microsoft Graph API
- Experience with multimodal AI solutions spanning text, image, and audio is preferred
- Ability to influence architecture and engineering decisions across teams and explain complex technical trade-offs to technical and non-technical stakeholders
- Demonstrated ability to mentor senior engineers, lead technical reviews, and establish reusable engineering patterns and standards
- Proficiency in Microsoft Office Suite skills
- Show an ownership mindset in everything you do; be a problem solver, be curious and inspired to take action, be proactive, and seek ways to collaborate and connect with people and teams in support of driving success
- Maintain a continuous growth mindset through relationships with stakeholders, experts, colleagues, and mentors, as well as structured courses and programs
- Where applicable, fluency in English and languages relevant to the working market
All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.
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