Key Responsibilities
- Design and implement enterprise-scale Generative AI and LLM-based solutions.
- Build RAG-based applications using vector databases and AI orchestration frameworks.
- Develop AI evaluation pipelines using DeepEval and Ragas.
- Optimize LLM performance through prompt engineering, evaluation, and monitoring.
- Define AI architecture standards, governance, and best practices.
- Collaborate with engineering teams to deliver scalable, production-ready AI systems.

Required Skills
- LLMs: OpenAI, Claude, Gemini, Llama, Mistral
- RAG, Agentic AI, Prompt Engineering, Multi-Agent Systems
- DeepEval & Ragas (Mandatory)
- LangChain, LlamaIndex, Hugging Face
- Vector Databases: Pinecone, Weaviate, Milvus, ChromaDB, FAISS
- Python, FastAPI, REST APIs, SQL




- AWS/Azure/GCP, Docker, Kubernetes, MLflow

Qualifications
- Bachelor's/Master's in Computer Science, AI, Data Science, or related field.
- 10+ years of software engineering experience with 4-5+ years in AI/Generative AI architecture.
- Proven experience designing enterprise AI platforms and LLM-based applications.
- Robust expertise in AI evaluation, cloud-native architecture, and scalable distributed systems.

Preferred: Knowledge of LLMOps, Knowledge Graphs, GraphRAG, AI Governance, AI Safety, and Enterprise Integrations.

📌 Enterprise AI Architect(Eval, DeepEval, Ragas)_Immediate (Bengaluru)
🏢 Kezan consulting
📍 Bengaluru