Responsibilities

  • Design and implement stateful, multi-agent workflows using LangGraph and the Google Agent Development Kit.
  • Develop generative AI applications that integrate enterprise data sources using Model Context Protocol (MCP) for secure LLM interaction.
  • Architect and deploy AI services on Google Cloud Platform using Vertex AI, Cloud Run, and Cloud Functions.
  • Build and maintain REST APIs in Python using frameworks such as FastAPI or Flask to expose AI capabilities.
  • Develop data pipelines, embeddings, and retrieval layers using BigQuery and vector databases.
  • Implement Retrieval-Augmented Generation architectures and establish evaluation mechanisms to monitor response quality, accuracy, and performance.
  • Optimize prompts, monitor model latency, and manage production workloads for reliability and cost control.
  • Maintain version control using Git and contribute to CI/CD pipelines for automated deployment.
  • Collaborate with product owners and platform teams while producing design documentation, runbooks, and production support during rollout.