– Applied AI Engineer / Senior AI Engineer / Lead Engineer

Employment Type: Full-Time (FTE)

Work Mode: Onsite

Location: Hyderabad & Indore

Notice Period: Immediate to 30 Days

Interview Process

- First Round: Virtual
- Final Round: Face-to-Face (F2F)

Job Summary

We are looking for hands-on Applied AI Engineers to build and maintain enterprise-grade, multi-agent AI platforms. The ideal candidates should have strong programming skills in Python and/or Java, along with practical experience in Generative AI, LLM-powered applications, Agentic AI, and Retrieval-Augmented Generation (RAG).

Key Responsibilities.

- Build and maintain individual AI agents such as Proofreader, Formatter, Document Converter, Paralegal, Reviewer/Approver, and Document Router.
- Implement multi-agent orchestration, task decomposition, tool/function calling, and inter-agent communication.
- Develop AI applications using frameworks such as LangChain, LangGraph, and Semantic Kernel.
- Build RAG pipelines, including document chunking, embeddings generation, and vector database integration.
- Implement agent-to-tool and agent-to-system integrations using Model Context Protocol (MCP).
- Develop and maintain enterprise-grade APIs, microservices, and integration layers.
- Work with REST APIs and implement secure authentication, RBAC, SSO, and audit logging.
- Collaborate with Business Analysts, Integration Engineers, DevOps Engineers, and QA teams.
- Support CI/CD pipelines,



Git version control, testing, and Agile/Scrum delivery.
- Ensure AI applications are secure, scalable, reliable, and production-ready.

Required Skills & Experience
- Strong programming skills in Python and/or Java.
- Hands-on experience in AI/ML, Generative AI, and LLM-powered applications.
- Practical experience building Agentic AI and multi-agent systems.
- Knowledge of LangChain, LangGraph, or Semantic Kernel.
- Experience with RAG pipelines, embeddings, and document chunking strategies.
- Experience with vector databases such as Azure AI Search, Qdrant, Pinecone, or similar.
- Familiarity with Model Context Protocol (MCP).
- Experience with REST APIs, microservices, and system integrations.
- Understanding of RBAC, SSO, authentication, audit logging, and secure coding practices.
- Exposure to document intelligence, OCR, document processing, and validation engines.
- Familiarity with A2A/UI frameworks and conversational AI solutions.
- Knowledge of Git, CI/CD pipelines, and Agile methodologies.

Preferred / Valuable to Have
- Experience in legal, professional services, or compliance-driven industries.
- Exposure to Databricks and multiple LLM providers such as OpenAI, Azure OpenAI, and Anthropic.
- Knowledge of LLM evaluation frameworks and LLM hosting/routing.
- Microsoft Certified: Azure AI Engineer Associate certification is an added advantage.

📌 AI Engineer (Indore)
🏢 EduRun Group
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