Google Cloud Generative AI Engineer (Vertex AI & Agentic AI)

Capgemini; Hyderabad; Hybrid; INR 1,500,000 - 2,300,000; Full time

Benefits offered by this job

Private Health Insurance

Pension Plan

Paid Time Off

Training & Development

Flexible work arrangements

Job summary

Capgemini is seeking a highly motivated Google Cloud Generative AI Engineer with 4-5 years of experience to design, develop, and deploy GenAI solutions on GCP. The role focuses on Vertex AI, Gemini models, LLM integration, and RAG architectures within enterprise-grade applications.

You will build scalable AI agents, integrate with enterprise systems, and contribute to CI/CD pipelines and cloud-native deployments while upholding security and governance standards.

Qualifications

• 4-8 years of software engineering, cloud app development, or AI/ML experience.
• 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, 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, BigQuery, and Cloud Storage.
• Knowledge of CI/CD practices, Git, Docker, and Kubernetes.
• Strong analytical, problem-solving, and communication skills.

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 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.

Skills

Python

REST APIs

Microservices

Prompt engineering

LLM orchestration

GCP

Vertex AI

Gemini models

Vector databases

Docker

Kubernetes

CI/CD

AI governance

Tools

Docker

Kubernetes

Git

BigQuery

Cloud Run

Pub/Sub

Job description

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, BigQuery, and Cloud Storage
• Knowledge of CI/CD practices, Git, Docker, and Kubernetes
• Strong 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 LangChain, LangGraph, 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:

• Competitive salary and performance-based bonuses
• Comprehensive benefits package
• Career development and training opportunities
• Flexible work arrangements (remote and/or office-based)
• Dynamic and inclusive work culture within a globally renowned group
• Private Health Insurance
• Pension Plan
• Paid Time Off
• 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 fast 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/