Google ADK GenAI Developer

• Design, develop, and deploy AI agents and multi-agent systems using Google ADK.
• Build enterprise GenAI applications using Google Gemini, Vertex AI, Python, and LLM technologies.
• Develop agent workflows, tool integrations, function calling, and autonomous decision-making capabilities.
• Design and implement RAG architectures using vector databases and enterprise knowledge sources.
• Integrate AI agents with REST APIs, databases, enterprise applications, and cloud services.
• Develop scalable microservices and cloud-native AI solutions.
• Implement AI governance, security, observability, monitoring, and responsible AI practices.
• Optimize LLM and agent performance for latency, scalability, reliability, and cost efficiency.
• Collaborate with architects, product owners, data engineers, and business stakeholders.
• Lead technical design discussions and mentor development teams on GenAI and agentic AI best practices.

We are seeking a highly skilled Google ADK GenAI Developer with 12+ years of software engineering experience and strong expertise in Generative AI, Python, Google Agent Development Kit (ADK), Google Gemini, and Vertex AI.

The ideal candidate will have hands-on experience designing and developing AI agents, multi-agent systems, RAG solutions, and enterprise GenAI applications using Google Cloud technologies. This role will focus on building scalable, secure, and production-ready AI solutions integrated with enterprise applications and data sources., * 12+ years of software development / engineering experience.

• Strong hands-on Python development experience.
• Hands-on experience with Google Agent Development Kit (ADK).
• Strong experience with Google Gemini and Vertex AI.
• Experience building AI Agents, Agentic AI, and Multi-Agent Systems.
• Strong knowledge of Generative AI, LLMs, Prompt Engineering, and RAG.
• Experience with function calling, tool calling, and agent orchestration.
• Experience with LangChain, LangGraph, MCP, AutoGen, or similar agent frameworks.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, or Vertex AI Vector Search.
• Strong understanding of REST APIs, microservices, and event-driven architectures.
• Hands-on experience with Google Cloud Platform (Google Cloud Platform).
• Experience with Docker, Kubernetes, CI/CD, and cloud-native development.
• Experience with SQL/NoSQL databases and enterprise integration patterns.

Preferred Skills

• Experience with AgentOps, LLM evaluation, AI observability, and monitoring.
• Knowledge of MLOps and AI model deployment.
• Experience with AI governance, responsible AI, security, and compliance.
• Google Cloud certifications.
• Experience working in Banking, Financial Services, Healthcare, or large enterprise environments.
• Knowledge of Neo4j, graph databases, and knowledge graphs.
• Experience with multimodal AI and AI-driven workflow automation.

Nice to Have

• Experience with Devin AI, Claude Code, GitHub Copilot, or similar AI-assisted development tools.
• Experience with advanced AI reasoning and agent orchestration frameworks.
• Experience building enterprise-grade AI automation solutions.