01Overview
Role Summary
Were looking for a highly motivated AI Engineer with 35, positive to have years of experience to help us build LLM-powered applications. This role is fully remote and will focus on using tools like LangChain, LangGraph, and open-source LLMs such as Ollama, LLaMA, Mistral, or Phi. You'll contribute to developing document understanding systems, intelligent chat agents, and multi-agent orchestration workflows.
What you will be doing:
Design, build, and deploy LLM-driven applications (e.g., document summarization, RAG-based QA, chatbots).
Work with open-source LLMs using platforms like Ollama and Hugging Face.
Implement LangChain and LangGraph workflows for multi-step, multi-agent task resolution.
Build and optimize RAG (Retrieval-Augmented Generation) systems using vector databases.
Collaborate with cross-functional teams to ship features to production.
Stay up-to-date with the latest in open-source LLMs, model optimization (LoRA, quantization), and multi-modal AI.
Required Skills
35 years of hands-on experience in AI/ML engineering.
Proficient in Python, PyTorch, and Hugging Face Transformers.
Proven experience with LangChain and LangGraph for LLM workflows.
Familiarity with Ollama, Mistral, LLaMA, or similar open-source LLMs.
Experience working with vector stores (Qdrant, Pinecone, Weaviate, FAISS).
Skilled in backend integration using FastAPI, Docker, and cloud platforms.
Solid grasp of NLP, LLM reasoning, prompt engineering, and document parsing.
Nice-to-Have
Experience with LangServe, OpenAI tool/function calling, or agent orchestration.
Background in multi-modal AI (e.g., image + text analysis).
Familiarity with MLOps tools (MLflow, Weights & Biases, Airflow).
Contributions to open-source GenAI projects.
Understanding of LLM safety, security, and alignment principles. .
