Job Title : AI Engineer - Agentic & RAG Systems(AI & Data Platforms)

Location : Remote,

Notice period : immediate to 30 days only can apply

- RAG Development & Optimization

- Chatbot Quality & Evaluation Frameworks

- Guardrails, Safety & Responsible AI. Multi-Agent Systems & Orchestration

- Design and implement Retrieval-Augmented Generation pipelines to ground LLMs in enterprise or domain-specific data.

- Make strategic decisions on chunking strategy, embedding models, and retrieval mechanisms to balance context precision, recall, and latency.

- Work with vector databases (Qdrant, Weaviate, pgvector, Pinecone) and embedding frameworks (OpenAI, Hugging Face, Instructor, etc.).

- Establish comprehensive evaluation frameworks for LLM applications, combining quantitative (BLEU, ROUGE, response time) and qualitative methods (human evaluation, LLM-as-a-judge, relevance, coherence, user satisfaction).

- Implement multi-layered guardrails across input validation, output filtering, prompt engineering, re-ranking, and abstention ("I don't know") strategies.

- Design and operate multi-agent workflows using orchestration frameworks such as LangGraph, AutoGen, CrewAI, or Haystack.

- Coordinate routing logic, task delegation, and parallel vs. sequential agent execution to handle complex reasoning or multi-step tasks.

- Strong proficiency in Python (FastAPI, Flask, asyncio) and GCP experience is good to have

- Demonstrated hands-on RAG implementation experience with specific tools, models, and evaluation metrics