Prompt Smart Solutions - AI & Generative AI Solution Architect

Description :

Must Have Skills :

GCP Cloud, AI, Gen AI, BigQuery, Dataflow, RAG

Competencies :

Non-Technical and Soft Skills :

- Strong problem-solving and analytical thinking

- Ability to explain complex AI concepts in simple, business-friendly terms

- High ownership mindset with comfort working in fast-paced, ambiguous environments

- Strong collaboration skills across sales, delivery, and partner teams

- Willingness to roll up sleeves and execute when needed.

Qualifications and Certifications :

- Bachelors or Masters degree in Engineering or Computer Science

- Google Cloud Professional Data Engineer or Professional Architect preferred

- AI, ML, or data certifications are a strong plus

Job Description :

Key Responsibilities: AI, GenAI, and Data Solutioning :

- Design and build end-to-end AI, GenAI, and data solutions on Google Cloud.

- Lead hands-on PoCs, pilots, and demos using Vertex AI, Gemini, and data platforms.

- Implement GenAI solution patterns such as RAG, agents, and LLM-based workflows.

- Translate business problems into working AI solutions with clear business outcomes.

- Develop reusable AI accelerators, reference implementations, and solution assets for sales support and customer engagement.

- Act as the AI technical authority in customer workshops, discovery sessions, and architecture reviews.

- Support strategic deals, RFPs, and executive-level pursuits from an AI and data perspective.

- Clearly articulate AI architecture, feasibility, value, and trade-offs to technical and non-technical audiences.

- Work closely with sales teams to shape AI-led solution narratives.

Google Cloud Collaboration

- Partner deeply with Google Cloud AI, data, and Gemini specialists on joint solutioning.

- Participate in Google-led innovation initiatives, pilots, and early adoption programs.

- Stay aligned with Google Cloud AI product roadmaps and emerging capabilities, internal capabilities, and solution development.

- Contribute to the organization's AI solution strategy and portfolio evolution.

Support enablement of sales, service lines, and delivery teams on AI and data solutions

- Mentor junior architects and engineers on AI and data best practices.

Technical Skills and Expertise: AI and GenAI :

- Strong hands-on experience with Vertex AI, Gemini, and GenAI solution architectures.

- Experience building LLM-based applications, including RAG and agent-based patterns

- Solid understanding of AI lifecycle management, governance, and MLOps.

- Ability to rapidly prototype AI solutions using Python and APIs and data platforms.

- Deep experience with BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage.

- Strong understanding of data pipelines, analytics platforms, and real-time data architectures.

- Experience integrating data platforms with AI and application layers : application and integration

- Strong Python skills and experience integrating AI services into applications.

- Experience with API-based architectures and microservices is a plus.

Non-Technical and Soft Skills :

- Strong problem-solving and analytical thinking.

- Ability to explain complex AI concepts in simple, business-friendly terms.

- High ownership mindset with comfort working in fast-paced, ambiguous environments.

- Strong collaboration skills across sales, delivery, and partner teams.

- Willingness to roll up sleeves and execute when needed.

Qualifications and Certifications :

- Bachelors or master's degree in engineering or computer science.

- Google Cloud Professional Data Engineer or Professional Architect preferred

- AI, ML, or data certifications are a strong plus.

Key Responsibilities :

Solutions, Strategy, and Ownership :

- Own the end-to-end Google Cloud solutions strategy for the organization, aligned to priority industries, AI-led plays, and growth objectives.

- Define and execute a solutions roadmap aligned with Google Cloud strategic priorities, including AI, Gemini, Data, and Industry Clouds.

- Lead the complete solution lifecycle from ideation and incubation to GTM readiness and scale.

- Ensure solutions are commercially viable, repeatable, differentiated, and measurable in impact.

- Continuously evolve solutions based on customer feedback, market trends, and learnings from active deals.

Operating in an organization Federated Service Line Model

- Act as the central orchestrator for Google Cloud solutions across the organization's service lines and industry units.

- Work closely with service line heads and practice leaders to co-create solutions leveraging service line strengths and assets.

- Align solution ownership, delivery models, and execution responsibilities across a matrixed organization.

- Ensure solutions are embedded into service line GTM motions and sales plays, not treated as standalone central initiatives.

- Influence stakeholders across the organization and drive alignment without direct authority.

Google Cloud Partnership and Co-Creation Leadership

- Serve as the primary solutions leadership interface with Google Cloud Partner Engineering, AI and Gemini specialists, and industry teams.

- Lead joint solution co-creation and roadmap alignment with Google Cloud.

- Drive early adoption of new Google Cloud capabilities through lighthouse customers, pilots, and reference implementations.

- Leverage Google Cloud funding programs for solution development, PoCs, and pilots to accelerate solution maturity and scale.

Good to Have Skills :

Data and AI Solution Support :

- Design and support data platforms using BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Storage.

- Support AI and GenAI solutioning, including model integration, pipelines, and application integration.

- Lead or support hands-on PoCs and pilots for data and AI use cases when required.

- Collaborate closely with the AI SME on advanced AI solution builds and customer engagements.

Application and platform modernization :

- Architect application modernization solutions, including containerization and re-platforming.

- Design solutions using GKE, Cloud Run, and modern application services.

- Support DevOps, CI/CD, and Infrastructure as Code implementations.

- Design cloud foundations that support data, AI, and application workloads.

Sales support and customer engagement :

- Support strategic sales pursuits and solution-led customer engagements.

- Participate in customer workshops, discovery sessions, and architecture reviews.

- Clearly explain solution architectures and trade-offs to technical and business stakeholders.

- Work closely with sales teams to shape solution narratives and technical positioning.