Overview

Job Title: AI/ML Engineer (LLMs, RAG & Agent Systems)

Responsibilities

• Design and implement components for LLM-based systems (retrievers, planners, memory, evaluators).
• Build and maintain RAG pipelines using vector databases and embedding models.
• Experiment with reasoning frameworks like ReAct, Tree of Thought, and Reflexion.
• Collaborate with backend and infra teams to deploy and optimize agentic applications.
• Research and experiment with open-source LLM frameworks to identify best-fit architectures.
• Contribute to internal tools for evaluation, benchmarking, and scaling AI agents.

Qualifications

• Strong foundation in ML/DL theory and implementation (PyTorch preferred).
• Understanding of transformer architectures, embeddings, and LLM mechanics.
• Practical exposure to prompt engineering, tool calling, and structured output design.
• Familiarity with RAG systems, vector databases, and API-based model inference.
• Ability to write clean, modular, and reproducible code.
• Hands-on with Hugging Face ecosystem (transformers, datasets, etc.).
• Working knowledge of Redis, PostgreSQL, or MongoDB.
• Familiarity with OpenAI, Anthropic, vLLM, or Ollama inference APIs.
• Exposure to MLOps concepts like CI/CD, model versioning, or cloud (AWS/GCP/Azure).
• Deep understanding of core principles over surface-level familiarity with tools.
• Ability to think like a researcher and execute like an engineer.
• Collaborative mindset, building together, learning together.