Google Cloud AI Engineer Jobs 2026 in India | Gemini Enterprise
Google has listed a Cloud AI Engineer opportunity within its Google Cloud Platform team. The role focuses on helping strategic customers adopt Gemini Enterprise and Google Cloud’s Agentic AI products by designing, deploying, and implementing production-ready AI solutions.
The position involves building generative AI applications, intelligent agents, and LLM-powered solutions; working directly with technical customers; and helping organizations transform workflows through AI. Candidates with experience in AI agents, cloud technologies, and customer-facing technical implementation can review the requirements and application details below.
Important: The provided job description does not specify an experience range, salary, or application deadline. Check the official Google Careers page for current availability and any additional requirements.
Google Cloud AI Engineer – Job Overview
| Company | |
| Team | Google Cloud Platform |
| Job Title | Cloud AI Engineer (English) |
| Job Location Options | Bengaluru, Karnataka; Gurugram, Haryana; Hyderabad, Telangana; Pune, Maharashtra, India |
| Qualification | Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience |
| Experience Range | Not specified in the provided listing |
| Core Focus | Generative AI, intelligent agents, Gemini Enterprise, Google Cloud Agentic AI |
| Customer Interaction | Direct technical customer engagement |
| Language Requirement | Fluent English communication |
| Interview Process | In-person interviews in most instances |
| Salary | Not disclosed in the supplied listing |
| Application Deadline | Not specified in the supplied listing |
About Google Cloud
Google Cloud provides cloud technology and enterprise solutions designed to help organizations transform their businesses. Its products support applications and infrastructure across the technology stack, with an emphasis on security, reliability, and scalability.
The Google Cloud Platform team works with developers, businesses, educational institutions, and government organizations to help them adopt cloud technologies and address business challenges.
In this Cloud AI Engineer role, the focus is on helping customers adopt Gemini Enterprise and Google’s broader Agentic AI suite. The position combines AI implementation, cloud architecture, technical problem-solving, and customer advisory responsibilities.
Cloud AI Engineer – Key Responsibilities
According to the supplied job description, the responsibilities include:
- Gemini Enterprise implementation: Deliver, deploy, and implement Gemini Enterprise solutions, using Agent Development Kits (ADKs) to solve complex technical customer challenges.
- Customer technical advisory: Act as a trusted technical advisor to Google’s strategic customers and help accelerate their adoption of Gemini Enterprise.
- Product troubleshooting: Provide guidance on existing product challenges and collaborate with engineering teams to address issues or identify possible workarounds.
- Technical presentations: Deliver recommendations and technical presentations adapted to different levels of business and technical stakeholders.
- Customer enablement: Proactively foster Gemini Enterprise adoption and enablement through technical guidance and recommendations.
- End-to-end execution: Lead the timely execution of Google Cloud Platform solution adoption for customers.
The role is designed for someone who can combine hands-on engineering with customer communication, technical architecture, and implementation support.
Minimum Qualifications
Candidates should meet the following minimum requirements listed for the position:
- Education: Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
- Generative AI experience: Experience building generative AI applications, intelligent agents, or LLM-powered solutions.
- Customer-facing experience: Experience working directly with technical customers.
- Communication: Ability to communicate fluently in English to support client relationship management.
The supplied listing does not state a specific number of years of experience or a graduation batch requirement. Applicants should check the official careers page for any additional eligibility details.
Preferred Qualifications and Technical Skills
The following experience and technical knowledge are listed as preferred qualifications. They may strengthen a candidate’s suitability for the role, but they are not presented as minimum requirements in the supplied description.
- AI agent development: Experience building and orchestrating agents using Agent Development Kits (ADKs) or frameworks such as LangChain, LlamaIndex, and AutoGen.
- Retrieval-Augmented Generation: Experience implementing RAG architectures and securely connecting LLMs with external productivity tools, including Google Workspace, and internal databases.
- Multimodal AI: Experience using LLMs to deploy solutions involving text, images, video, and voice.
- Enterprise AI platforms: Experience deploying, configuring, and managing enterprise-grade generative AI platforms, particularly Gemini Enterprise.
- Security and governance: Understanding of security, governance, and compliance requirements for enterprise AI deployments.
- Cloud computing: Knowledge of serverless execution environments, virtualization, hosted services, multi-tenant cloud infrastructures, and secure cloud networking.
Preferred Work Locations
When applying, candidates will have an opportunity to share their preferred working location from the following options:
- Bengaluru, Karnataka, India
- Gurugram, Haryana, India
- Hyderabad, Telangana, India
- Pune, Maharashtra, India
The listing notes that in most instances, the hiring process requires in-person interviews. Candidates should confirm interview arrangements and any location-specific requirements through the official recruitment process.
How to Prepare for the Cloud AI Engineer Role
Applicants interested in this position can prepare by reviewing the technical and customer-facing areas highlighted in the job description:
- Build or demonstrate a generative AI application or intelligent agent that solves a practical problem.
- Understand agent orchestration and the role of ADKs or frameworks such as LangChain, LlamaIndex, and AutoGen.
- Practise designing a RAG workflow, including retrieval, grounding, and secure access to data sources.
- Review enterprise AI security, governance, and deployment considerations.
- Prepare examples of technical troubleshooting and explaining complex systems to customers or stakeholders.
- Strengthen English communication skills for technical presentations and customer discussions.
These are preparation suggestions based on the listed responsibilities and preferred qualifications, not additional formal eligibility conditions.
Salary and Benefits
Salary: The supplied job description does not disclose a compensation figure. Candidates should refer to the official Google Careers listing or recruitment team for salary and benefits information.
The provided description also does not specify a particular bonus, insurance package, relocation benefit, or other compensation component for this role. Applicants should verify the applicable package during the recruitment process.
How to Apply for Google Cloud AI Engineer Jobs
Interested candidates can review the official job listing and submit an application through Google Careers, if the vacancy is still accepting applications.
- Open the official Google Careers job page using the link below.
- Review the minimum qualifications and preferred technical skills carefully.
- Prepare an updated resume highlighting generative AI applications, agent development, LLM solutions, cloud implementation, and customer-facing technical work where applicable.
- Include relevant projects that demonstrate AI architecture, troubleshooting, secure data integration, or production deployment experience.
- Submit the application through the official Google Careers portal and provide your preferred working location from the listed options.
- Check the recruitment communication for interview instructions. The listing states that in-person interviews are required in most instances.
Application note: The supplied job description does not include a deadline or confirm the current application status. Check the official careers page before applying and rely on Google’s recruitment communication for the latest details.
Frequently Asked Questions (FAQs)
1. What qualification is required for Google’s Cloud AI Engineer role?
Answer: The minimum qualification is a Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience. Experience building generative AI applications, intelligent agents, or LLM-powered solutions is also required.
2. Which locations are available for the Google Cloud AI Engineer position?
Answer: The listing provides Bengaluru, Gurugram, Hyderabad, and Pune as preferred working location options. Candidates can share their preferred location when applying.
3. Is the Google Cloud AI Engineer job suitable for freshers?
Answer: The supplied description does not specify a fresher eligibility rule or an experience range. It requires experience building generative AI applications, intelligent agents, or LLM-powered solutions and working directly with technical customers. Candidates should check the official listing for any additional experience requirements.
Explore More Job Opportunities
Looking for more technology jobs, internships, and recruitment updates? Explore these sections for additional opportunities:
Keep building practical AI projects, strengthen your cloud and agent-development skills, and prepare to explain technical solutions clearly to customers. Share this opportunity with professionals who have experience in generative AI, LLM applications, and cloud engineering.