AI Engineer

Advanced Prompt Engineering, Context Engineering skills, Python skills.
Hands-on experience building agentic AI solutionsusing Google ADK + LangChain/LangGraph, including orchestration and tool usage patterns, Kafka, Gepa Optimizer, Agent Harness
Strong Python development skills for backend services, workflow engines, and AI pipelines.
Advanced SQL/PostgresSQL proficiency(complex joins, window functions, query optimization).
Experience with RAG architectures and integrating LLMs with enterprise data sources (vector stores + relational systems).
Production-grade engineering practices: testing, CI/CD, logging, monitoring, and error handling, Github, Copilot
Prompt engineering / Prompt finetuning

Mandatory Key Skills

1. Python – Strong hands-on development experience
2. Agentic AI – Hands-on experience building AI agents and agentic workflows
3. Google ADK (Agent Development Kit)
4. LangChain / LangGraph – Agent orchestration, workflows, state management and tool calling
5. Advanced Prompt Engineering & Context Engineering
6. RAG (Retrieval-Augmented Generation) – Enterprise-grade RAG implementation
7. Vector Databases / Vector Stores – Integration with LLM/RAG solutions
8. SQL / PostgreSQL – Complex joins, window functions and query optimization
9. Kafka – Integration with event-driven/backend AI workflows
10. Production Engineering – Testing, CI/CD, logging, monitoring and error handling