AI Consultant Agentic AI (D

5 - 8 years

14 - 18 Lacs

Posted:3 days ago| Platform: Naukri logo

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Job Description


We are seeking a highly skilled AI Consultant to join our Agentic AI Center of Excellence (CoE) within AI-Labs. This role is pivotal in designing, building, and maintaining data pipelines and AI application components that support cutting-edge Agentic AI Proof-of-Concept (POC) solutions within the CoE. Successful candidates would be expected to enable data readiness, integration, and model deployment using Microsoft Azure technologies to power enterprise-scale AI use cases.
 
Key Responsibilities:

Data Pipeline Engineering: Design, build, and maintain ingestion, transformation, and storage pipelines using Azure Data Factory, Synapse Analytics, and Data Lake. AI Data Enablement: Collaborate with AI Consultants to prepare and manage datasets for supervised, unsupervised, and synthetic learning workflows.

POC Support: Implement optimized data pipelines for Agentic AI POCs using realistic or synthetic data sources. API & Microservices Development: Build RESTful APIs and Fast API-based microservices for data access and model interaction within Azure-hosted environments. Model Deployment Support: Enable end-to-end deployment of AI models using Azure Machine Learning, Azure Kubernetes Service (AKS), and Azure DevOps. Data Governance & Compliance: Ensure data quality, lineage, and compliance with responsible AI and enterprise data standards.
Role Requirements and Qualifications:
5+ years of experience in data engineering and Azure cloud ecosystem. Strong hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Blob Storage, Azure Machine Learning, Azure DevOps, Azure Kubernetes Service.

Experience supporting with GPT model fine-tuning, data preparation for LLMs, synthetic data generation, Vector/Graph DBs (neo4j), Azure AI Search, LangChain data loaders. Context engineering for agent memory and tool chaining and responsible AI principles, model explainability, data privacy controls. Programming expertise in Python, PySpark, SQL, Fast API (Pydantic, REST APIs), ETL/ELT workflows, data modeling, schema design, feature engineering.

Containerization using Docker/Kubernetes, and CI/CD automation. Ability to collaborate effectively with AI Consultants, Architects, and Business Analysts. Strong communication skills to explain data engineering concepts to non-technical stakeholders & ability to transfer industry knowledge to peers.
Preferred Certifications:
Microsoft Certified: Azure Data Engineer Associate (DP-203). Microsoft Certified: Azure AI Engineer Associate (AI-102). SnowPro Data Engineer or other relevant specialization in Data Engineering, Generative AI, or Agentic AI frameworks.

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