Description

· Core Engineering & Programming: Strong software engineering fundamentals with expert-level proficiency in Python. Experience with Java, Go, or TypeScript is a strong plus.
· LLM & GenAI Application Development: Proven, hands-on experience building and deploying production-grade applications using Large Language Models (LLMs) like GPT, Claude, or Gemini. This must go beyond simple API calls and include experience with tool/function-calling, structured outputs, and evaluation.
· Agentic AI Frameworks & Orchestration: Demonstrable expertise in designing and implementing agentic workflows using frameworks like LangGraph, Semantic Kernel, AutoGen, or similar. Experience with multi-agent systems, planning, and autonomous execution is critical.
· RAG (Retrieval-Augmented Generation): Deep, practical knowledge of building and optimizing RAG pipelines. This includes data ingestion, various chunking strategies, embeddings, vector databases (e.g., Pinecone, Chroma, FAISS), and hybrid search/reranking.
· Production & MLOps: Experience with production engineering practices, including building scalable APIs (REST, RPC), microservices, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (AWS, Azure, or GCP).

 

Key Skills

Education

Any Gradute