Senior Gen AI Engineer (R-18859)

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. We are looking for an experienced AI Engineer to design, build, and operationalize AI driven solutions for our global Analytics organization. The ideal candidate will have strong hands-on expertise in Python, PySpark, agentic workflow development, and modern GenAI frameworks, with experience building scalable applications using LLMs, retrieval systems, and automation pipelines.  Key Responsibilities:

Agent Development & Architecture

Build agentic workflows using LangChain/LangGraph and similar frameworks.

Develop autonomous agents for data validation, reporting, document processing, and domain workflows.

Deploy scalable, resilient agent pipelines with monitoring and evaluation.

GenAI Application Engineering

Develop GenAI applications using models like GPT, Gemini, and LLaMA.

Implement RAG, vector search, prompt orchestration, and model evaluation.

Partner with data scientists to productionize POCs.

Data & Platform Engineering

Build distributed data pipelines (Python, PySpark).

Develop APIs, SDKs, and integration layers for AI-powered applications.

Optimize systems for performance and scalability across cloud/hybrid environments.

MLOps / LLMOps

Contribute to CI/CD workflows for AI models—deployment, testing, monitoring.

Implement governance, guardrails, and reusable GenAI frameworks.

Collaboration & Stakeholder Engagement

Work with analytics, product, and engineering teams to define and deliver AI solutions.

Participate in architecture reviews and iterative development cycles.

Support knowledge sharing and internal GenAI capability building. 

Key Skills:

5–8 years of experience in AI/ML engineering, data science, or software engineering, with atleast 2 years focused on GenAI.

Strong programming expertise in Python, distributed computing using PySpark, and API development.

Hands on experience with LLM frameworks (LangChain, LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs).

Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestration.

Solid understanding of GenAI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineering.

Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AI.

Strong problem solving, system design thinking, and ability to translate business needs into scalable AI solutions.

Excellent verbal, written communication and presentation skills.