About the role

Job Title: Presales AI Solution Architect

Domain: Presales

Technology: Google AI services (AI Studio, Vertex AI, and Gemini Enterprise)

Experience:

7 to 8 years in AI architecture or Presales solutions roles.

Required: minimum 4 years focused on Google’s AI service offerings.

Work Type: Office and Field only

Job Role:

As a Presales Solution Architect at Ingram Micro, you'll be more than just a technical expert — you'll be a trusted advisor to our partners, guiding them through the journey of adopting AI services. Your primary focus will be to identify, develop, and close opportunities by working closely with our sales and marketing teams and applying your technical consulting and solutioning-led skills.

You'll engage with partners and end customers at various levels, from decision-makers to technical teams, ensuring they understand the value proposition of Google’s AI solutions. By aligning their needs with our solutions, you'll drive the transition from traditional models to AI-integrated services, driving multi-year subscription buy-ins. By sharing best practices and insights, you'll contribute to the continuous improvement of our services.

Your contributions will be instrumental in the successful materialization of the sales opportunities, upselling, thereby contributing to the revenue.

Responsibilities:

Participate in pre-sales activities, including solutioning, cost estimation, proposal presentations, and partner enablement sessions.
Should be able to work independently on the Presales RFP/RFI to build solution proposals.
Drive AI initiatives leveraging a broad range of Google AI services and solutions to improve performance and efficiency (perform discovery engagements, conduct workshops to identify AI opportunities, and define AI adoption paths).
Architect solutions on Google-based AI platform and services offerings: Develop comprehensive Statements of Work (SOWs), technical architectures, and cost models aligned with Google partner funding requirements (DAF/PAP).
Collaborate with stakeholders to articulate solution concepts and influence teams.
Mentor partner engineering team and enforce best practices.
Working closely with the sales team to qualify leads, present the solution effectively, answer technical questions, accompany the sales team to customer/partner locations across India (need basis) for partner/customer meetings, and represent Ingram Micro at various events/workshops.

Skills:

Strong working experience in Presales with a focus on Google’s AI platform and solutions, including:
- Gemini Models: Enterprise and Gemini 2.5 Flash (low latency, cost-efficient) and Gemini 2.5 Pro (enhanced reasoning) for enterprise use cases.
- Vertex AI Platform: Build custom AI applications with model customization, tuning, RAG implementations, and multimodal capabilities.
- Google Agentspace: Architect enterprise knowledge management solutions with agentic intranet search, custom agent creation, and pre-built agents.
- Generative Media: Implement Imagen 4 (image generation), Veo 3 (video generation), and Lyria (text-to-music) for creative workflows.
Proven experience with designing and presenting innovative solutions leveraging Gemini Enterprise, Gemini (Flash & Pro), Google Agentspace, and Vertex AI to solve complex business challenges.
Hands-on expertise with enterprise integration and migration of greenfield Google Cloud foundations and landing zone builds with AI-ready infrastructure.
Design scalable data architecture using:
- BigQuery (Autonomous data-to-AI platform with Gemini-powered data agents for conversational analytics),
- AlloyDB, Looker (Conversational BI platform with Gemini integration for LookML code generation and visualizations),
- Dataflow, Pub/Sub, Dataproc (real-time and batch data processing pipelines).
Capability to design solutions using Google Unified Security, security agents for alert triage and malware analysis, and Cloud Confidential Eligible (CCE) applications.
Produce comprehensive technical documentation, architecture diagrams, and runbooks.
Exposure to Google Cloud Platform, legacy database modernization, and multi-cloud architecture with Cross-Cloud Interconnect.
Strong logical thinking and problem-solving skills.
Proficiency in English (written and spoken).

Certifications:

Required: Google Certified - Professional Machine Learning Engineer
Optional: Google Cloud Certified, Professional Cloud Architect, Professional Data Engineer.

Education:

Degree or higher in Computer Science or Engineering, or a related field.

Solution Architect - Cloud Sales (Google)