Are you looking for a Google Cloud AI Engineer job opportunity in India? Google is hiring for the position of Cloud AI Engineer, offering an opportunity to work with generative AI, intelligent agents, Gemini Enterprise, and Google Cloud technologies.
This role is designed for professionals who have experience building AI-powered applications and helping technical customers implement cloud-based AI solutions. The selected candidate will work with strategic customers to design production-ready architectures, deploy Gemini Enterprise solutions, troubleshoot complex AI agent behavior, and support the adoption of Google’s agentic AI technologies.
The Google Cloud AI Engineer position is listed across multiple locations in India, including Bengaluru, Gurugram, Hyderabad, and Pune. Candidates should have a bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience. Experience developing generative AI applications, intelligent agents, or large language model (LLM)-powered solutions is also required.
In this article, we cover the complete Google Cloud AI Engineer job description, including eligibility criteria, responsibilities, required skills, preferred qualifications, job locations, and the official application process.
- 1 Google Cloud AI Engineer Recruitment 2026: Job Overview
- 2 About the Google Cloud AI Engineer Job
- 3 What Does a Google Cloud AI Engineer Do?
- 4 Google Cloud AI Engineer Eligibility Criteria 2026
- 5 What Is Retrieval-Augmented Generation (RAG)?
- 6 What Is Agentic AI?
- 7 Is Google Cloud AI Engineer Suitable for Freshers?
- 8 Google Cloud AI Engineer Salary
- 9 Google Cloud AI Engineer Job Locations in India
- 10 Final Words
Google Cloud AI Engineer Recruitment 2026: Job Overview
Here are the important details based on the supplied Google job description.
| Particulars | Details |
|---|---|
| Company | |
| Job Title | Cloud AI Engineer |
| Job Category | Google Cloud / AI Engineering |
| Job Locations | Bengaluru, Gurugram, Hyderabad, and Pune, India |
| Educational Qualification | Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience |
| Required Experience | Experience building generative AI applications, intelligent agents, or LLM-powered solutions |
| Customer Interaction | Experience working directly with technical customers |
| Language Requirement | Fluent English communication |
| Key Technologies | Gemini Enterprise, Google Cloud, Agent Development Kits (ADKs), LLMs |
| Preferred Skills | RAG, AI agent frameworks, multimodal AI, cloud computing |
| Work Arrangement | Not specified in the supplied job description |
| Salary | Not specified in the supplied job description |
| Employment Type | Not specified in the supplied job description |
| Application Deadline | Not specified in the supplied job description |
| Interview Process | In-person interviews are required in most instances |
Candidates searching for Google Cloud AI Engineer jobs in India should note that this is not described as a fresher-specific position. The minimum qualifications include practical experience building AI applications and working directly with technical customers.
About the Google Cloud AI Engineer Job
Google Cloud provides cloud infrastructure, platforms, and AI technologies that help organizations modernize their operations and develop new digital capabilities.
As businesses increasingly adopt generative AI, they need professionals who can turn AI capabilities into secure, useful, and production-ready applications. The Google Cloud AI Engineer role supports this process by helping customers implement Gemini Enterprise and other products from Google’s agentic AI portfolio.
The position combines technical implementation, AI architecture, customer engagement, troubleshooting, and solution adoption. Rather than focusing only on model development, the engineer will help customers integrate AI into their workflows and overcome technical challenges during deployment.
The role also involves working with Google’s engineering teams when customers encounter product limitations or complex technical issues. This requires a combination of hands-on technical expertise, communication skills, and an understanding of enterprise requirements.
For professionals experienced in generative AI, LLM applications, and cloud technologies, this opportunity may offer a chance to work on enterprise AI implementations across different industries.
What Does a Google Cloud AI Engineer Do?
A Cloud AI Engineer helps customers design, implement, deploy, and improve AI-powered applications using Google Cloud technologies.
For example, an organization might want to build an AI assistant that can answer questions using internal documents, retrieve information from business databases, or automate selected workflows. An engineer in this role would help determine the technical approach, connect the required data sources, implement the solution, and troubleshoot problems during deployment.
The work may involve Gemini Enterprise, AI agent frameworks, Retrieval-Augmented Generation (RAG), cloud infrastructure, security considerations, and enterprise integrations.
The Google Cloud AI Engineer position also involves explaining technical concepts to customers, advising them on implementation practices, and helping them achieve successful adoption of AI solutions.
Google Cloud AI Engineer Eligibility Criteria 2026
Candidates should review the minimum qualifications carefully before applying.
Educational Qualification
Applicants must have a bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
The supplied description does not specify a minimum CGPA, mandatory graduation year, or particular degree percentage.
Generative AI Experience
Candidates must have experience building one or more of the following:
- Generative AI applications
- Intelligent agents
- LLM-powered solutions
This is a key requirement for the role. Applicants should be able to explain the systems they have built, the technologies used, the challenges encountered, and how their solutions addressed a particular problem.
Technical Customer Experience
The job description requires experience working directly with technical customers.
Candidates should be comfortable understanding customer requirements, discussing implementation approaches, resolving technical concerns, and communicating recommendations.
English Communication
Fluent English communication is required to support client relationship management.
Applicants should be prepared to explain technical designs, discuss trade-offs, present recommendations, and communicate effectively with different stakeholders.
What Is Retrieval-Augmented Generation (RAG)?
RAG is a technique that allows a generative AI application to retrieve relevant information from external sources before generating an answer.
For example, a company may want an AI assistant to answer questions using its internal policies, technical documentation, or product manuals. A RAG system can retrieve relevant documents and provide their content as context to the language model.
A typical RAG workflow includes:
- Collecting and preparing documents.
- Splitting content into manageable sections.
- Creating searchable representations, often using embeddings.
- Retrieving relevant content for a user’s question.
- Supplying the retrieved information to the language model.
- Generating and evaluating the response.
In enterprise environments, the system must also respect access permissions and protect confidential information.
Because the Google Cloud AI Engineer role prefers RAG implementation experience, candidates should understand both the architecture and the practical challenges involved in building reliable retrieval-based applications.
What Is Agentic AI?
Agentic AI refers to systems that can use models, tools, and defined workflows to pursue a goal through multiple steps.
A conventional chatbot may respond to a question with text. An AI agent may be able to interpret a task, retrieve information, call an approved tool, evaluate the result, and continue through additional steps.
Enterprise AI agents must be designed carefully. Developers need to consider permissions, error handling, monitoring, human oversight, and the boundaries of what an agent is allowed to do.
For the Google Cloud AI Engineer position, knowledge of agent development is valuable because the role involves helping customers adopt Google’s agentic AI products and solve complex implementation challenges.
Is Google Cloud AI Engineer Suitable for Freshers?
The supplied job description does not explicitly identify this vacancy as a fresher role. Although a bachelor’s degree or equivalent practical experience is accepted, candidates must also have experience building generative AI applications, intelligent agents, or LLM-powered solutions and working directly with technical customers.
Therefore, applicants should not assume that the position is intended for candidates with no relevant experience.
Professionals who have built AI projects, deployed LLM applications, implemented RAG systems, or supported customer-facing technical implementations may find the requirements more closely aligned with their background.
Candidates with academic or personal projects should describe their experience accurately and verify whether it meets Google’s practical experience expectations.
Google Cloud AI Engineer Salary
The salary for the Google Cloud AI Engineer position is not specified in the supplied job description.
Compensation can depend on factors such as job level, location, relevant experience, and the overall employment package. The listing provided does not establish a salary range or specific benefits for this vacancy.
Candidates should refer to the official Google careers page or discuss compensation with the recruitment team during the hiring process. Avoid relying on unverified salary figures published by third-party websites.
Google Cloud AI Engineer Job Locations in India
Google lists the following preferred working locations for this position:
- Bengaluru, Karnataka
- Gurugram, Haryana
- Hyderabad, Telangana
- Pune, Maharashtra
The application process allows candidates to share their preferred working location from the listed options.
The supplied description does not confirm a remote or hybrid arrangement. Candidates should verify the final work location and office attendance expectations during the application process.
Google also notes that in-person interviews are required in most instances. Applicants should be prepared for this possibility when planning their recruitment process.
Final Words
The Google Cloud AI Engineer Job Description 2026 highlights an opportunity for professionals with experience in generative AI, LLM-powered applications, intelligent agents, and customer-facing technical implementation.
The position focuses on deploying Gemini Enterprise solutions, designing production-ready AI architectures, supporting enterprise integrations, troubleshooting agent behavior, and helping customers adopt Google’s AI technologies.
Candidates with practical AI engineering experience, knowledge of RAG and agent frameworks, cloud computing skills, and strong communication abilities should review the minimum qualifications carefully before applying.
