GenAI Engineer

• 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.