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We are seeking a highly motivated Google Cloud Generative AI Engineer with 4-5 years of experience in designing, developing, and deploying AI-powered applications on Google Cloud Platform (GCP). The ideal candidate will have hands-on expertise in Google Agent Development Kit (ADK), Vertex AI, Gemini models, LLM integration, RAG architectures, and cloud-native application development. This role involves building scalable AI solutions, intelligent agents, and enterprise-grade GenAI applications that drive business innovation. Key Responsibilities - Build and implement Generative AI applications leveraging Vertex AI, Gemini models, Agent Builder, and other Google AI services. - Design, develop, and deploy AI agents and multi-agent systems using Google Agent Development Kit (ADK). - Integrate AI agents with enterprise applications, APIs, databases, and third-party systems. - Develop orchestration workflows for autonomous, conversational, and task-driven AI agents. - Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources. - Collaborate with business stakeholders, architects, and product teams to gather requirements and translate them into scalable AI solutions. - Optimize prompts, agent behavior, context management, and model performance to improve business outcomes. - Ensure adherence to security, compliance, governance, and responsible AI practices. - Monitor, troubleshoot, and enhance production AI applications for performance, reliability, and scalability. - Participate in architecture reviews and recommend best practices for AI/ML and cloud-native solutions. - Contribute to CI/CD pipelines, automation, and infrastructure deployment for AI workloads on GCP. - Stay current with emerging GenAI technologies, frameworks, and Google Cloud innovations. Requirements - 4- 8 years of experience in software engineering, cloud application development, or AI/ML solutions. - Hands-on experience with Google Cloud Platform (GCP) services. - Strong expertise in Vertex AI, Gemini models, Model Garden, and AI application deployment. - Experience with Google ADK (Agent Development Kit) for building agentic AI systems. - Proficiency in Python and experience with REST APIs and microservices. - Experience implementing RAG architectures, vector databases (Vertex AI Vector Search, Pinecone, Weaviate, ChromaDB, etc.), and semantic search solutions. - Understanding of prompt engineering, LLM evaluation, and AI agent orchestration. - Experience with cloud-native technologies including Cloud Run, GKE, Pub/Sub, Cloud Functions, Big Query, and Cloud Storage. - Knowledge of CI/CD practices, Git, Docker, and Kubernetes. - Robust analytical, problem-solving, and communication skills. Preferred Qualifications - Google Cloud certifications such as Professional Cloud Developer, Professional Cloud Architect, or Professional Machine Learning Engineer. - Experience with Lang Chain, Lang Graph, CrewAI, or other agentic AI frameworks. - Familiarity with enterprise integration patterns and API management. - Experience implementing AI governance, observability, and monitoring frameworks. - Understanding of MLOps and LLMOps best practices. Benefits Competitive compensation and benefits package: 1. Competitive salary and performance-based bonuses 2. Comprehensive advantages package 3. Career development and training opportunities 4. Flexible work arrangements (remote and/or office-based) 5. Dynamic and inclusive work culture within a globally renowned group 6. Private Health Insurance 7. Pension Plan 8. Paid Time Off 9. Training & Development Note: Benefits differ based on employee level. About Capgemini Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the rapid evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group 22.5 billion in revenues in 2023. https://www.capgemini.com/us-en/about-us/who-we-are/ .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.