Data Scientist

Dun & Bradstreet; Hyderabad; Hybrid; INR 2,500,000 - 5,500,000; Full time

Job summary

Dun & Bradstreet in Hyderabad is seeking an experienced AI/ML engineer to architect GenAI applications and scalable agent pipelines. You will design agentic workflows, data validation, and document processing with LangChain, LangGraph, and modern LLM frameworks, delivering reliable production systems.

You will collaborate with data scientists and product teams, implement MLOps practices, and optimize cloud/hybrid deployments across AWS/Azure/GCP.

Qualifications

• 8-12 years of experience in AI/ML engineering, data science, or software engineering, with at least 2 years focused on GenAI.
• Strong programming expertise in Python and distributed computing (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.

Responsibilities

• 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.
• 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.
• 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.
• Contribute to CI/CD workflows for AI models deployment, testing, monitoring.
• Implement governance, guardrails, and reusable GenAI frameworks.
• 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.

Skills

Python

PySpark

Distributed computing

API development

Problem solving

Cloud platforms

LLM concepts

Communication skills

Education

M.Tech / MS in CS / AI

PhD (nice-to-have)

Tools

LangChain

LangGraph

Transformers

OpenAI SDK

Vertex/Bedrock SDKs

Docker

AWS/Azure/GCP

Job description

Key Responsibilities:

1. 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.

2. 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.

3. 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.

4. MLOps / LLMOps:

• Contribute to CI/CD workflows for AI modelsdeployment, testing, monitoring.
• Implement governance, guardrails, and reusable GenAI frameworks.

5. 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 Requirements:

• 8-12 years of experience in AI/ML engineering, data science, or software engineering, with at least 2 years focused on GenAI.
• Strong programming expertise in Python, distributed computing using PySpark, and API development.
• Hands on experience withLLM 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.

Good to Have:

• Experience in workflow automation and building reusable AI components.
• Background in analytics, statistical models, or enterprise data products.
• Experience with MLOps / LLMOps tooling