Senior GenAI Engineer – Google ADK / Gemini
Quick Overview
Job Description
Job Overview
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.
Key Responsibilities
- 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.
Required Skills
- 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.
Skills
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