AI Solution Architect

Compunnel, Inc.; Columbia (MD); Remote; USD 120,000 - 150,000; Full time

Job summary

A leading tech consulting firm is looking for an AI Solution Architect to develop next-generation AI platforms on Google Cloud. The role requires strong technical skills in AI development and the ability to collaborate with cross-functional teams. You will design AI infrastructure and support the implementation of scalable AI solutions. The ideal candidate is skilled in Google Cloud tools, has a deep engineering background, and is eager to take on broader architectural responsibilities.

Qualifications

• Strong hands-on experience with Google Cloud, including Vertex AI, Gemini models, and multimodal AI capabilities.
• Deep engineering background capable of designing and building AI solutions.
• Experience or readiness to expand into broader architectural roles.

Responsibilities

• Design and implement AI infrastructure on Google Cloud leveraging Vertex AI and related tools.
• Collaborate with product management and engineering teams for scalable AI solutions.
• Document solution trade-offs and present findings to leadership.

Skills

Google Cloud

Vertex AI

Gemini models

GenAI frameworks

Analytical skills

Problem-solving

Tools

Azure DevOps

BigQuery

AlloyDB

Cloud Storage

Job description

The AI Solution Architect will play a hands-on role in designing, building, and evolving next-generation AI platforms on Google Cloud.

This position is ideal for a senior engineer or emerging architect who thrives in a fast-paced, innovation-driven environment and is ready to expand into broader architectural responsibilities while remaining deeply technical.

The role focuses on developing GenAI and agentic AI solutions using Vertex AI, Gemini, and Google Cloud’s AI ecosystem, as well as evaluating external platforms when needed to meet business requirements.

The architect will collaborate closely with product management, engineering teams, and internal stakeholders to deliver scalable AI solutions that support automation, AI agents, and enterprise AI capabilities across the organization.

Key Responsibilities

• Design and implement AI infrastructure on Google Cloud, leveraging Vertex AI, Gemini models, BigQuery, AlloyDB, and Cloud Storage.
• Explore and test emerging Google Cloud AI features and apply them to real-world use cases.
• Compare GCP-native capabilities with third-party SaaS or marketplace solutions, identifying the right balance between managed services and custom development.
• Define evaluation criteria, benchmarks, and architectural scorecards.
• Lead proofs of concept (POCs), RFIs/RFPs, and vendor assessments.

Analysis, Governance & Alignment

• Document solution trade-offs and present findings to leadership.
• Collaborate with enterprise architects to assess compatibility with existing AI infrastructure.
• Ensure adherence to data security, privacy, governance, and compliance requirements.
• Coordinate approvals with legal, compliance, and architecture governance teams.

Solution Implementation & Delivery

• Support procurement and onboarding of selected AI tools and platforms.
• Implement solutions within the organization’s AI infrastructure to ensure optimal business alignment.
• Operate within an Agile delivery framework using Azure DevOps and enterprise standards.
• Manage vendor relationships to monitor performance and resolve issues.

Strategic Contribution & Leadership Support

• Communicate recommendations, timelines, and project updates to leadership and stakeholders.
• Advise on build-versus-buy decisions and long-term AI platform strategy.
• Define reference architectures and integration models for AI solutions.
• Contribute to governance documents, evaluation templates, and architectural best practices.
• Participate as a reviewer/advisor in architecture and AI governance forums.

Required Qualifications

• Strong hands-on experience with Google Cloud, including:
• Vertex AI (pipelines, training, endpoints, feature store)
• Gemini models and multimodal/agentic AI capabilities
• GenAI and agentic AI frameworks
• Deep engineering background with the ability to design, build, and prototype AI solutions.
• Experience or readiness to grow into broader architectural responsibilities.
• Strong analytical and problem-solving skills with the ability to evaluate alternatives inside and outside Google Cloud.
• Continuous learning mindset, staying updated on the latest AI and cloud advancements.
• Ability to work independently in a remote environment.

Preferred Qualifications

• Experience working with AI-driven automation or AI agents.
• Background collaborating with product management and engineering teams.
• Familiarity with enterprise AI data platforms and integration patterns.