Tech Stack

Description

You will lead the design, development, and scaling of next-generation Agentic AI systems and GenAI applications, owning the technical direction and bridging cutting-edge LLM capabilities with production-grade software. You will architect multi-agent systems, define best practices for RAG pipelines, and lead backend and cloud-native infrastructure on GCP.

Requirements

• 5+ years software engineering, 2-3+ years building production-grade AI/LLM systems
• Expert-level Python with asynchronous programming (AsyncIO)
• Experience designing and implementing RAG pipelines, vector search, and GenAI systems
• Deep experience with FastAPI and PostgreSQL/vector databases
• Hands-on experience with GCP, Docker, Kubernetes, and CI/CD

Responsibilities

• Lead design of agentic architectures including multi-agent orchestration, tool usage, planning, memory, and self-reflection using Google ADK
• Define and standardize RAG architectures with retrieval strategies, context engineering, hybrid search, re-ranking
• Design evaluation frameworks for model performance (hallucination rates, precision/recall)
• Architect scalable backend systems and APIs using FastAPI
• Lead cloud-native AI solutions on GCP using Docker, Kubernetes, and CI/CD pipelines