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# Google Antigravity Consultant

- **Company:** Radyant Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** LangGraph Framework, JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Cloud Computing, Cloud Engineering, Code Generation, Code Review, Continuous Integration, Software Debugging, DevOps, Programming Tools, Github, Python (Programming Language), Secure Coding, Software Deployment, Software Engineering, Systems Integration, TypeScript, Web Application Frameworks, Software Repository, Google Cloud, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, AI Coding Agents, Agentic-AI, Git, Kubernetes, Google Gemini, Restful APIs, Model Context Protocol, Terraform, Docker, Microservices
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/e2f93a4a-a87d-4c7b-8060-32f72d23bb29

## About the Role

* 5+ years of experience in software development, cloud engineering, or AI solution implementation.
 * Hands-on experience with Google Antigravity or comparable agentic AI development environments.
 * Strong understanding of Agentic AI, Generative AI, Large Language Models (LLMs), and AI coding agents.
 * Experience with Google Gemini APIs, AI SDKs, and prompt engineering.
 * Proficiency in Python, JavaScript, or TypeScript.
 * Experience with VS Code-based development environments and AI coding assistants.
 * Strong knowledge of REST APIs, microservices, and application integration.
 * Experience with Git, GitHub, CI/CD, Docker, and DevOps practices.
 * Working knowledge of Google Cloud Platform, including Vertex AI, Cloud Run, and Cloud Functions.
 * Understanding of AI agent orchestration, tool calling, context management, and workflow automation.
 * Strong troubleshooting, architecture, documentation, and communication skills.

Preferred / Nice-to-Have Skills

 * Experience with Google Agent Development Kit (ADK).
 * Familiarity with Model Context Protocol (MCP) and AI tool integrations.
 * Experience with LangChain, LangGraph, or other agent orchestration frameworks.
 * Knowledge of retrieval-augmented generation (RAG) and vector databases.
 * Experience implementing AI governance and secure enterprise AI solutions.
 * Familiarity with Kubernetes, Terraform, and cloud-native architecture.
 * Experience leading AI development platform adoption or enterprise AI transformation initiatives.

## Description

We are seeking an experienced Google Antigravity Consultant with strong expertise in AI-assisted software development, agentic AI workflows, cloud technologies, and modern application engineering.
The ideal candidate will have hands-on experience with Google Antigravity, Google's agent-first development platform, and the ability to leverage AI coding agents to automate development tasks, accelerate application delivery, optimize engineering workflows, and integrate AI-powered solutions into enterprise environments., * Implement and configure Google Antigravity for AI-driven application development and engineering workflows.

 * Design and manage autonomous AI coding agents for software development, debugging, testing, and deployment.
 * Leverage Google Gemini models and agentic AI capabilities to enhance developer productivity.
 * Build and optimize AI-assisted development workflows across IDE, terminal, and browser environments.
 * Integrate Google Antigravity with existing development tools, Git repositories, APIs, and CI/CD pipelines.
 * Develop enterprise-grade applications using Python, JavaScript, TypeScript, and modern frameworks.
 * Design and implement multi-agent workflows for complex software engineering tasks.
 * Work with Google Cloud Platform (Google Cloud Platform) services for AI application development and deployment.
 * Implement secure development practices, access controls, code review processes, and AI governance standards.
 * Evaluate AI-generated code for quality, performance, reliability, and security.
 * Collaborate with engineering, DevOps, architecture, and business teams to identify AI automation opportunities.
 * Conduct technical workshops, proof-of-concepts (POCs), and knowledge-transfer sessions.