Agentic AI Solution Architect (Google Cloud)

Employment Type: Full-Time

Benefits: Enterprise-grade Fortune 500 benefits

Work Style: Hybrid (2 days onsite weekly)

Travel: Up to 30% (consulting engagements)

Eligible Locations: New York, Chicago, Dallas, San Francisco, Los Angeles, Seattle, Washington, D.C.

Primary Office: New York City

Our client is investing heavily in intelligent, agent-driven platforms and is looking for a senior Agentic AI Solution Architect to help define how these systems are designed, documented, and delivered at scale.

This role sits at the intersection of AI architecture, cloud engineering, and collaborative delivery. You will shape reusable agent patterns, guide solution design, and ensure architectural clarity across teams building on Google Cloud.

Your Focus Areas

1. Agent Systems & Architectural Patterns

• Create and evolve architectures for autonomous, multi-agent AI systems.
• Define standard patterns that support coordination, reasoning, memory, and tool usage.
• Design cloud-native AI solutions leveraging GCP services such as Vertex AI, GKE, BigQuery, Pub/Sub, and Cloud Functions.

2. Architecture Communication & Design Artifacts

• Develop clear architecture diagrams, technical models, and design specifications.
• Convert complex AI concepts into build-ready documentation for delivery teams.
• Maintain architectural consistency with enterprise platform standards.

3. Platform Alignment & Enterprise Integration

• Embed security, compliance, and scalability requirements into solution designs.
• Ensure agent-based solutions integrate smoothly with existing platforms and services.
• Continuously refine designs as platform capabilities and business needs evolve.

4. Collaborative Delivery & Design Validation

• Support collaborative requirements definition and iterative design validation.
• Contribute architecture inputs to agile delivery cycles and testable design models.
• Partner with engineering, product, and business teams to align on priorities.

What Success Looks Like

• Agent architectures are reusable, well-documented, and production-ready.
• Engineering teams can implement designs with minimal friction or rework.
• Platform standards are consistently applied across AI solutions.
• Stakeholders clearly understand architectural decisions and tradeoffs.

Experience & Capabilities

Agentic AI Expertise

• Designing autonomous and multi-agent systems with planning, coordination, and decision logic.
• Hands-on experience with agent patterns such as RAG, planner–executor, orchestrator–worker, and collaborative agents.
• Familiarity with agent interoperability standards (MCP, A2A).

Cloud & Engineering

• Strong hands-on experience with Google Cloud AI and data services (Vertex AI, BigQuery, Pub/Sub, GKE).
• Ability to design scalable, secure AI systems optimized for agent workflows.
• Advanced Python development; working knowledge of Java and Go.
• Experience across data pipelines, MLOps, and AI lifecycle management.

Design & Collaboration

• Proven ability to produce high-quality diagrams and technical documentation (Lucidchart, Visio, Confluence, Jira).
• Comfortable working in Agile environments with cross-functional teams.
• Strong communicator who can bridge technical depth and business clarity.

Added Advantage

• Google Cloud certifications (Cloud Architect, ML Engineer, or Data Engineer).
• Exposure to reinforcement learning or advanced multi-agent techniques.
• Familiarity with responsible AI and governance frameworks.
• Prior experience supporting collaborative architecture or design governance processes.

Why This Role Stands Out

You’ll help define how intelligent agent systems are built—not just once, but repeatedly and consistently—across an enterprise. This role offers influence, technical depth, and the chance to work at the forefront of agent-based AI on Google Cloud.