AI Engineer (Agents Focus)

Role Overview

Senior AI Engineer will lead the development of multi-agent systems. Responsibilities include agent design, RAG, tool-calling, evaluation, safety guardrails, and integration with the core platform.

Key Responsibilities

• Architecture and implementation of LLM agents (LangChain, CrewAI, LangGraph).
• Development of RAG systems (Pinecone/Weaviate/Chroma).
• Prompt engineering, chain-of-thought, tool-calling.
• Agent evaluation (Ragas, DeepEval, Langfuse/Phoenix).
• Implementation of safety (prompt injection defense, human-in-the-loop).
• Integration with backend (FastAPI, Celery), monitoring of latency/token costs.

Requirements

Must-Have

• 4+ years in AI engineering, 2+ years specifically on LLM-based systems.
• Deep experience with agent frameworks: LangChain / CrewAI / LangGraph (multi-agent orchestration, tool-calling, state management).
• Hands-on RAG systems (vector DB: Pinecone, Weaviate, Chroma; retrieval strategies, chunking).
• Expertise in prompt engineering + evaluation (Ragas, DeepEval, Langfuse/Phoenix).
• Strong Python (3.10+, async, API integrations).
• Understanding of LLM safety (guardrails, hallucination mitigation, bias handling).

Nice-to-Have

• Production multi-agent systems experience.
• Knowledge of classical ML (scikit-learn, XGBoost/LightGBM) and NLP (Hugging Face Transformers, spaCy) for hybrid solutions.
• MLOps tools (MLflow, Kubeflow, Evidently).