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Agentic / LLM-Focused AI Engineers

Role:

Agentic / LLM-Focused AI Engineers

Location:

Indore CITP, Pune - Baner, Pune - Viman Nagar

Experience:

2+ years

Key Skills:

Crew AI, Agentic AI


What will your role look like
  • Design, develop, and implement agentic AI solutions using frameworks like LangGraph, CrewAI, or similar ecosystems.
  • Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines, leveraging Knowledge Graphs and Vector Databases.
  • Integrate LLM-powered applications with frontend systems, APIs, or enterprise platforms.
  • Collaborate with cross-functional teams to transform business use cases into intelligent, context-aware AI applications.
  • Iterate on AI agent workflows, ensuring scalability, reliability, and measurable outcomes in production environments.


Why you will love this role
  • Opportunity to work on cutting-edge agentic AI, LLMs, and next-generation intelligent systems.
  • A chance to influence architectural decisions and shape the future of AI-driven solutions.
  • Exposure to modern AI frameworks and RAG technologies used by top AI engineering teams.
  • A collaborative culture that values innovation, experimentation, and continuous learning.
  • Work on high-impact, real-world projects that push the boundaries of applied AI.


We would like you to bring along
  • Strong proficiency in Python for AI/ML application development.
  • Solid understanding of Large Language Models, prompt engineering, and LLM integration patterns.
  • Hands-on experience with frameworks such as LangGraph, CrewAI, LlamaIndex, LangChain, or similar.
  • Experience with Vector Databases (Pinecone, FAISS, Weaviate, etc.) and working knowledge of Knowledge Graphs.
  • Ability to design, build, iterate, and productionize AI agents with a strong engineering mindset.
  • Working knowledge of React or Angular for integrating AI features into front-end interfaces (good to have).

Good-to-have skills
  • Experience with public cloud platforms (AWS, Azure, GCP).
  • Understanding of MLOps practices for deploying and monitoring LLM/AI applications.
  • Familiarity with API development or backend services supporting AI workflows.

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