Artificial Intelligence Engineer

Shift Timings - 1pm to 10pm or 3pm to 12am

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

· 3–5 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.