- Build LLM-powered chatbots using OpenAI, RAG, tool calling, and agent frameworks (LangChain, LangGraph).
- Design Agent-to-Agent (A2A) architectures for multi-step reasoning and autonomous workflows.
- Design retrieval pipelines using vector databases.
- Implement hallucination reduction techniques including grounding, re-ranking, citations, and confidence scoring.
- Work with finance and enterprise datasets ensuring accuracy and governance.
- Deploy and monitor AI systems using cloud-native and MLOps practices.
- Implement CI/CD for AI pipelines and inference services.

Requirements

Must-Have:

- Python.
- AI/ML experience.
- Experience with LLMs such as OpenAI (GPT-4/4.1), Anthropic, Gemini, Llama.
- Agentic AI frameworks like LangGraph, LangChain,



MCP, Agent-to-Agent (A2A) patterns.
- RAG & Search technologies including embeddings, hybrid search, cross-encoders.
- Vector databases.
- Cloud experience with AWS services (Code Pipeline - CICD, S3, EC2, ECS, Lambda, SageMaker).
- SQL.

Nice-to-Have:

- Evaluation & Observability tools such as LangSmith, MLflow, Weights & Biases.
- Data tools like Snowflake, DBT, structured & unstructured data pipelines.
- Experience with prompt/version management and offline & online LLM evaluation.

📌 GenAI Engineer (Bengaluru)
🏢 Accelon Consulting
📍 Bengaluru