Agentic AI Engineer-F2F Interview

Design, build, and deploy AI agentic systems using LLMs (OpenAI, Anthropic, Llama, etc.).

Develop autonomous multi-agent workflows, memory systems, and decision-making pipelines.

Build modular and reusable Python components for agent cognition, planning, tools, and actions.

Integrate agents with APIs, databases, vector stores, automation tools, and cloud services.

Implement prompt engineering, RAG pipelines, and reasoning-enhanced agent behaviors.

Optimize agent performance, response quality, reliability, and tool-use accuracy.

Develop backend services, microservices, and REST APIs to support AI applications.

Use frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, FastAPI, etc.

Implement best practices for version control, testing, observability, and deployment.

Collaborate with product, ML, and engineering teams to design intelligent AI solutions.

Stay current with emerging agentic architectures, LLM capabilities, and automation trends.