Offshore AI Engineer

Job Role: Offshore AI Engineer

Experience: 5+ Years

Role Overview

We are seeking an experienced AI Engineer with 5+ years of hands-on experienceto design and implement enterprise-grade data and AI solutions. This role is code-focused and involves building data pipelines in Microsoft Fabric, developing custom AI workflows with LangChain, and deploying models in Azure AI Foundry. The engineer will also be responsible for creating agentic AI systems, applying NLP techniques, and leveraging vector databases to power retrieval-augmented generation (RAG) and intelligent automation.

Key Responsibilities

• Build scalable data pipelines and workflows in Microsoft Fabric (Lakehouse, Dataflows Gen2, Notebooks, Pipelines).
• 
  
• Develop custom AI workflows and orchestrations using Python and LangChain (RAG pipelines, multi-agent systems).
• 
  
• Deploy, monitor, and integrate models using Azure AI Foundry.
• 
  
• Design and implement agentic AI systems for automation, decision support, and client use cases.
• 
  
• Apply NLP techniques (text preprocessing, embeddings, classification, summarization).
• 
  
• Integrate and optimize vector databases (Azure AI Search, Pinecone, Weaviate, FAISS) for retrieval and memory.
• 
  
• Collaborate with consultants and business teams to deliver AI solutions tailored to client needs.

Required Skills & Experience

• Minimum 5 years of experience

  in data engineering, AI engineering, or cloud-based solution development.
• 
  
• Strong expertise in Microsoft Fabric for enterprise data engineering.
• 
  
• Proficiency in Python development (automation, AI/ML integration, data workflows).
• 
  
• Experience with LangChain or similar orchestration frameworks.
• 
  
• Hands-on experience with Azure AI Foundry (model deployment, vector store integration).
• 
  
• Practical knowledge of NLP methods and their application in enterprise AI solutions.
• 
  
• Experience working with vector databases for retrieval and grounding.
• 
  
• Background in Azure Cloud engineering (resource provisioning, scaling, monitoring).

Preferred Skills

• Experience with applied machine learning (training, fine-tuning, evaluation).
• 
  
• Integration of AI/data pipelines with ERP/Finance systems (Oracle, D365, NetSuite).
• 
  
• Prior consulting or client-facing delivery support.

Success Criteria

• Delivery of scalable, production-ready data and AI pipelines in Fabric.
• 
  
• Development of custom agentic AI and RAG systems using NLP and vector databases.
• 
  
• Offshore capability established for technical AI engineering with minimal U.S. oversight.