AI Agent Engineer - Google ADK & Generative AI

Key Responsibilities

• Design, develop, and deploy intelligent AI agents using Google Agent Development Kit (ADK).
• Build scalable multi-agent systems capable of planning, reasoning, tool orchestration, and autonomous task execution.
• Integrate AI agents with Google Workspace services, including Gmail, Drive, Docs, Sheets, Calendar, Meet, and Chat.
• Develop secure integrations with enterprise applications, REST APIs, databases, and external services.
• Design and implement Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories and vector databases.
• Build conversational memory, session management, and context-aware interactions for AI agents.
• Optimize prompts, reasoning strategies, and tool selection to improve agent accuracy and reliability.
• Deploy and manage AI solutions on Google Cloud Platform (GCP), including Vertex AI and related cloud services.
• Implement authentication, authorization, and secure access using OAuth 2.0, IAM, and enterprise security standards.
• Develop monitoring, logging, tracing, and evaluation frameworks to ensure production reliability.
• Collaborate with cross-functional teams to identify automation opportunities and deliver AI-driven business solutions.
• Stay current with advancements in Generative AI, LLMs, AI agents, and cloud technologies.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
• 5+ years of software engineering experience developing enterprise applications.
• 2+ years of hands-on experience building Generative AI or Large Language Model (LLM) solutions.
• Practical experience with Google Agent Development Kit (ADK).
• Experience developing applications using Google Gemini models.
• Strong programming skills in Python.
• Experience building RESTful APIs and microservices.
• Hands-on experience designing AI agents or workflow orchestration frameworks.
• Strong understanding of Prompt Engineering, Function Calling, and AI Agent architectures.
• Experience implementing Retrieval-Augmented Generation (RAG).
• Experience working with Vector Databases.
• Experience with Google Cloud Platform (GCP).
• Experience with Git, CI/CD pipelines, and Agile development methodologies.

Preferred Qualifications

• Experience deploying AI solutions using Vertex AI Agent Engine.
• Experience integrating Google Workspace APIs.
• Experience with LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar AI orchestration frameworks.
• Knowledge of Model Context Protocol (MCP).
• Experience with Docker and Kubernetes.
• Experience working with BigQuery, Firestore, Cloud SQL, or AlloyDB.
• Familiarity with AI observability, evaluation frameworks, and LLMOps practices.
• Experience building enterprise copilots or AI assistants.