– Generative AI (GenAI) / LLM Engineer

Experience: 3-4 Years

Role: GenAI / LLM Engineer

Job Summary

We are looking for a skilled GenAI / LLM Engineer with hands-on experience in developing and implementing AI-powered applications using Large Language Models (LLMs). The candidate should have strong Python programming skills and experience building solutions using Generative AI, Retrieval-Augmented Generation (RAG), prompt engineering, and AI frameworks.

Key Responsibilities

- Design, develop, and implement Generative AI applications using LLMs.
- Build and integrate LLM-based solutions using OpenAI, Azure OpenAI, or similar models.
- Develop RAG-based applications to retrieve relevant information from documents and databases.
- Work with frameworks such as LangChain and LangGraph.
- Develop and integrate REST APIs using Python.
- Work with vector databases for storing and retrieving embeddings.
- Implement prompt engineering techniques to improve AI model responses.
- Optimize application performance, accuracy, scalability, and response time.
- Collaborate with engineering and business teams to deliver AI-powered solutions.
- Deploy and maintain AI applications in cloud environments.

Required Technical Skills
- Strong hands-on experience in Python programming.




- Experience working with Generative AI and Large Language Models (LLMs).
- Practical experience with OpenAI / Azure OpenAI APIs or equivalent LLM platforms.
- Hands-on experience building RAG (Retrieval-Augmented Generation) applications.
- Knowledge of LangChain / LangGraph or similar AI frameworks.
- Experience with Vector Databases such as Pinecone, FAISS, ChromaDB, or Weaviate.
- Understanding of Prompt Engineering, embeddings, and semantic search.
- Experience developing REST APIs using FastAPI or Flask.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.

Positive to Have
- Experience with AI Agents and multi-agent architectures.
- Knowledge of Machine Learning and Deep Learning concepts.
- Experience with Docker, Kubernetes, and CI/CD.
- Familiarity with LLM evaluation, monitoring, and performance optimization.
- Experience with Hugging Face and open-source LLM models.

Ideal Candidate A hands-on engineer who has developed and deployed real-world GenAI applications, particularly using Python, LLMs, RAG, and AI frameworks, rather than having only theoretical knowledge or experience using AI tools.

📌 AI Engineer (Pune)
🏢 Creospan
📍 Pune