AI / LLM Application Engineer

Role & responsibilities

3-5 years of experience in Python-based application development with exposure to AI/LLM solutions

• Hands-on experience building LLM applications using LangChain and/or LangGraph
• Strong understanding of LLM concepts, prompt engineering, embeddings, transformers, and vector search
• Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions
• Experience with vector databases such as Pinecone, FAISS, Weaviate, or similar
• Knowledge of machine learning fundamentals and frameworks such as Scikit-learn, PyTorch, or TensorFlow
• Experience developing and deploying REST APIs, Docker-based applications, and CI/CD pipelines
• Exposure to cloud platforms such as GCP,
• Understanding of agentic workflows, tool integration, and multi-step reasoning systems
• Strong problem-solving, debugging, and collaboration skills
• Exposure to MLOps, monitoring, and production support is a pluss