WE

Weekday

Senior AI Engineer

Job summary

Delhi

Work model

Hybrid · 3 days home
1 week ago
Job description

This role is for one of our clients

Company Name: Whilter.AI

Industry: Technology, Information and Media

Seniority level: Mid-Senior level

Location: Gurgaon, Delhi, Bangalore (Hybrid)

Job Type: Full-time

Compensation: ₹12,00,000 - ₹25,00,000 a year

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.