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.
