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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Engineer - Google Agentic AI (ADK, Agent Development & Deployment - **Company:** Recutify Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Confluence, JIRA, BigQuery, Software as a Service, Cloud Computing, Continuous Integration, Data Integration, Memory Management, Github, Graph Database, Identity and Access Management, Python (Programming Language), Machine Learning, Performance Tuning, Salesforce.Com, Search Technologies, Microsoft SharePoint, Software Deployment, Software Engineering, Strategies of Testing, Data Logging, Google Cloud, Enterprise Software Applications, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Web Filtering, Event Driven Architecture, Kubernetes, Information Technology, Machine Learning Operations, Virtual Agents, Software Coding, Restful APIs, Terraform, Api Management, Docker, Servicenow - **Published:** July 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=05c6391111870424 ## About the Role * Bachelor's or master's degree in computer science, Engineering, AI, Data Science, or related field. * 10 15 years of software engineering experience. * Minimum 2 3 years of hands-on experience building GenAI, Agentic AI, or LLM-based solutions. * Google Cloud certifications preferred: + Professional Cloud Architect + Professional Machine Learning Engineer + Generative AI Leader/Engineer Certifications ## Description We are seeking a highly skilled Google Agentic AI Engineer to design, develop, deploy, and operate enterprise-grade AI agents using Google Agent Development Kit (ADK), Vertex AI Agent Builder, Gemini Models, and Google Cloud Platform (GCP). The candidate will be responsible for building intelligent, scalable, secure, and production-ready multi-agent systems that integrate with enterprise applications, APIs, and knowledge repositories., Agent Development * Design and develop AI agents using Google ADK. * Build autonomous and multi-agent workflows leveraging Gemini models. * Implement agent orchestration, memory management, session handling, and tool integrations. * Develop custom tools, function calling mechanisms, and API integrations for enterprise use cases. * Design agent collaboration patterns using A2A and MCP standards. * Build reusable agent templates and frameworks to accelerate solution delivery. Agent Deployment & Operations * Deploy agents using Vertex AI Agent Builder and Agent Engine. * Build scalable production deployments on GCP services including Cloud Run, GKE, and Vertex AI. * Implement agent observability, monitoring, tracing, logging, and performance optimization. * Define SLIs, SLOs, and operational dashboards for AI workloads. * Support production operations, incident management, and continuous improvement initiatives. Enterprise AI Solutions * Develop RAG solutions by leveraging Vertex AI Search, Vector Search, and enterprise knowledge sources. * Integrate agents with enterprise systems such as Salesforce, ServiceNow, SharePoint, Jira, Confluence, and custom APIs. * Implement context engineering, knowledge graph integration, and enterprise grounding techniques. * Build workflow automation agents, diagnostic agents, customer support assistants, and operational bots. Security, Governance & Compliance * Design secure AI architectures following enterprise governance standards. * Implement guardrails, content filtering, hallucination detection, DLP, access control, and identity management. * Ensure compliance with enterprise security, privacy, and regulatory requirements. * Drive AI governance, monitoring, risk management, and responsible AI practices. Engineering Excellence * Establish coding standards, evaluation frameworks, and testing strategies for AI agents. * Mentor engineering teams on Agentic AI architecture and development best practices. * Conduct architecture reviews and technical assessments. * Stay current with advancements in Agentic AI, LLMs, ADK, MCP, A2A, LangGraph, CrewAI, and related ecosystems. Mandatory Skills Google Agentic AI * Strong hands-on experience with: + Google Agent Development Kit (ADK) + Vertex AI + Vertex AI Agent Builder + Agent Engine + Gemini Models + Gemini API + Multi-Agent Systems + Agent Orchestration + Agent Memory & Sessions + Tool Calling and Function Calling AI/LLM Engineering * Prompt Engineering * RAG Architecture * Vector Databases * Knowledge Graphs * Agent Evaluation Frameworks * LLM Fine-Tuning and Optimization * AI Observability and Monitoring Cloud & Development * Google Cloud Platform (GCP) * Python * REST APIs * Kubernetes (GKE) * Cloud Run * Docker * GitHub Actions / CI-CD * Infrastructure as Code (Terraform preferred) Data & Integration * BigQuery * Vertex AI Search * Vector Search * Enterprise API Integration * MCP and A2A Protocols Preferred Skills * LangGraph * LangChain * CrewAI * LlamaIndex * OpenAI / Anthropic / Gemini ecosystems * AI Security & Governance * MLOps / LLMOps * Event-driven architecture * Real-time AI applications * Enterprise SaaS integrations * AI Cost Optimization ## Related Videos - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [Designing and Deploying Distributed Multimodal Multi-Agent Systems with Google's AI Stac](https://www.wearedevelopers.com/videos/1976-designing-and-deploying-distributed-multimodal-multi-agent-systems-with-google-s-ai-stac) ## Related Articles - [Got AI ideas but no money? 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