Gen AI Engineer

We are hiring a highly skilled Senior AI Engineer / Agentic AI Engineer with strong experience delivering enterprise-scale AI solutions in Banking or Financial Services. The ideal candidate will have hands-on expertise in building Agentic AI systems, Generative AI pipelines, and production-grade Conversational AI / RAG platforms on Microsoft Azure.

You will work on real-world banking use cases such as Conversational AI, Document Intelligence, Agentic Workflow Automation, and Multimodal AI systems serving large user bases.

Key Responsibilities

• Design and implement Agentic AI architectures for banking-grade enterprise applications

• Build scalable Generative AI / RAG pipelines using Azure OpenAI and Azure AI Search

• Deliver production-grade AI systems with high availability, security, and performance

• Implement multimodal and multilingual AI solutions (Text + Vision, including English / Arabic)

• Develop document processing pipelines using Azure AI Document Intelligence

• Build Computer Vision workflows using OpenCV

• Develop REST APIs using FastAPI and deploy using Docker and Azure Containers

• Design embedding, vector search, and hybrid retrieval strategies

• Integrate Azure Cosmos DB / Document DB

• Implement CI/CD pipelines and Git-based workflows

• Collaborate closely with business stakeholders and engineering teams to deliver end-to-end AI solutions

Requirements

Mandatory Skills

• 5+ years of hands-on experience in AI / ML / Generative AI / Agentic AI

• Prior experience implementing AI solutions in Banking or Financial Services, delivering enterprise-scale, production-grade systems

• Strong expertise in Python and SQL

• Microsoft Azure Cloud experience including: Azure OpenAI, Azure AI Search, Azure AI Document Intelligence, Azure Vision, Azure AI Foundry

• Agentic / LLM frameworks: LangGraph, LangChain

• Advanced Prompt Engineering

• Computer Vision using OpenCV

• API development using FastAPI

• Git, Docker, Azure Container Services

• Azure Cosmos DB / Document DB

• CI/CD pipelines

Good to Have

• Open-source AI technologies (YOLO models, Deep Learning, NLP)

• Agent orchestration frameworks: Semantic Kernel, Microsoft Agentic Framework

• LLM evaluation metrics and frameworks (RAG evaluation, custom benchmarks, etc.)

• MCP (Model Context Protocol)

• Orkes (Agentic AI Workflow Automation Tool)

• Streamlit or Flask for rapid PoC development

• Microsoft Certification: Azure AI Engineer (AI-102)

Preferred Candidate Profile

• Strong system design and architecture mindset
  
• Experience working on large-scale enterprise AI platforms
  
• Comfortable owning end-to-end delivery (design → build → deploy → scale)
  

Benefits