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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.

Designation: AI Intern
Location: Mumbai
Function: Operations
SBU: AI & Automation
Tenure: 3 months

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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• Collaborate with cross-functional teams to design, develop, and deploy end-to-end Agentic AI solutions for diverse enterprise use cases.

• Build and maintain robust, scalable middleware and microservices that seamlessly integrate APIs, AI/ML models, databases, and cloud platforms.

• Ensure the reliability, observability, security, compliance, and performance of AI systems in production environments through effective monitoring and governance practices.

• Mentor junior engineers, provide technical guidance, and contribute to the development of internal AI frameworks, accelerators, and enablement initiatives.
• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.

• Demonstrated expertise in Python, PySpark, Generative AI technologies, RAG architectures, LangGraph, LangChain, and prompt engineering.

• Hands-on experience working with cloud-native solutions on AWS and/or GCP.

• Knowledge of vector databases such as Qdrant and Chroma is a strong advantage.

• Solid understanding of version control systems and collaborative development practices using Git, GitHub, and Bitbucket.

• Ability to translate business requirements into scalable, production-ready AI solutions and contribute effectively within agile teams.