Senior AI Engineer

Position: Senior AI Engineer
Experience: 6–9 Years
Location: Gurgaon & Bangalore (Hybrid)
Employment Type: Full-Time

About the Role

We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy next-generation AI applications powered by Large Language Models (LLMs), Agentic AI frameworks, and cloud-native architectures. The ideal candidate will have deep expertise in AI/ML engineering, Agent-to-Agent (A2A) systems, MCP protocol integration, and scalable Azure-based deployments.

This role requires hands-on experience building production-grade AI solutions using modern frameworks such as LangChain and LangGraph, along with strong software engineering and cloud architecture skills.

Key Responsibilities

• Design, develop, and deploy enterprise-grade AI/GenAI solutions leveraging LLMs and Agentic AI architectures. 


• Build and orchestrate multi-agent workflows using Agentic Layer A2A frameworks and MCP Protocol. 


• Develop intelligent applications utilizing vector embeddings, prompt engineering, context engineering, and retrieval strategies. 


• Create scalable AI pipelines using LangChain, LangGraph, and related AI orchestration frameworks. 


• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and search platforms. 


• Deploy and manage AI services on Azure Cloud, ensuring high availability, security, and performance. 


• Develop and maintain Azure Functions, Azure Container Apps, and cloud-native microservices. 


• Integrate and optimize data storage solutions including Azure AI Search, VectorDBs, Redis, Cosmos DB, Blob Storage, and Iceberg. 


• Collaborate with product, engineering, and data teams to translate business requirements into AI-driven solutions. 


• Monitor, troubleshoot, and optimize AI systems for scalability, latency, accuracy, and cost efficiency. 


• Establish best practices for AI application architecture, testing, deployment, and governance. 

Required Skills & Qualifications

Must Have

• 6–9 years of experience in Software Engineering, AI/ML Engineering, or related domains. 


• Strong hands-on experience with Python and proficiency in Java.  


• Experience building AI/GenAI applications using LangChain and LangGraph. 


• Expertise in: 
  
  
  
  • Prompt Engineering 
  
  
  • Context Engineering 
  
  
  • Vector Embeddings 
  
  
  • RAG Architectures 
  
  
  • LLM Integration 
  
  
  
  


• Hands-on experience with Agentic AI frameworks, Agent-to-Agent (A2A) communication, and MCP Protocol. 


• Strong experience deploying solutions on Microsoft Azure Cloud.  


• Experience with: 
  
  
  
  • Azure AI Search 
  
  
  • Vector Databases 
  
  
  • Redis 
  
  
  • Cosmos DB 
  
  
  
  


• Experience building and managing: 
  
  
  
  • Azure Functions 
  
  
  • Azure Container Apps 
  
  
  
  


• Strong understanding of cloud-native architectures, distributed systems, scalability, and performance optimization. 

Good to Have

• Experience with Azure Blob Storage and Apache Iceberg. 


• Exposure to MLOps and AI observability tools. 


• Experience with Kubernetes, Docker, and CI/CD pipelines. 


• Knowledge of multi-agent orchestration and autonomous AI systems. 


• Familiarity with AI security, governance, and responsible AI practices.