> Markdown version of [/jobs/ext/4346977-google-adk-developer](https://www.wearedevelopers.com/jobs/ext/4346977-google-adk-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Google ADK Developer

- **Company:** Cognizant Technology Solutions Corporation
- **Location:** Durham, NC, United States
- **Experience:** Experienced
- **Salary:** $80,000.0 - $100,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Unit Testing, Cloud Computing, Code Review, Databases, Continuous Integration, Software Debugging, Python (Programming Language), Object-Oriented Software Development, Performance Tuning, Cloud Services, Software Engineering, Systems Integration, Data Logging, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Agentic-AI, Git, Containerization, Integration Tests, Google Cloud Functions, Virtual Agents, Restful APIs, Docker, Agent2Agent Protocol
- **Published:** October 22, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3472086949&tx=FK906PFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 3-7 years of software development experience.
 * Experience with Python and object-oriented programming principles.
 * Hands-on knowledge of Google ADK, Vertex AI, LangChain, or similar AI frameworks.
 * Understanding of REST APIs, cloud-native application development, and containerization.
 * Familiarity with CI/CD pipelines, Git, Docker, and cloud deployment practices.
 * Knowledge of LLMs, prompt engineering, RAG, and agent-based architectures.

## Description

Agent Development

 * Develop and maintain AI agents using Google ADK and Vertex AI services.
 * Build agent workflows, tools, prompts, and integrations with external systems.
 * Implement multi-agent communication mechanisms using MCP and A2A protocols.
 * Develop reusable libraries and components to accelerate agent development.

Engineering & Testing

 * Create unit tests, integration tests, and evaluation frameworks for agentic applications.
 * Support debugging, troubleshooting, and performance optimization activities.
 * Implement logging, monitoring, and observability capabilities.
 * Participate in CI/CD and deployment activities.

Cloud & Platform Operations

 * Deploy and manage AI solutions on Google Cloud platforms.
 * Configure Cloud Run, APIs, databases, and supporting cloud services.
 * Support production monitoring and incident resolution activities.
 * Ensure compliance with security, governance, and operational standards.

Collaboration & Learning

 * Collaborate with architects, managers, and fellow engineers throughout the software development lifecycle.
 * Participate in code reviews, design discussions, and knowledge-sharing activities.
 * Stay current with emerging AI agent frameworks, tools, and cloud technologies.