Solution Architect, Agentic AI, NYC

About the position West Monroe is seeking a highly skilled Solution Architect to lead the end-to-end design and development of Agentic use cases & prototypes on Google Cloud Platform (GCP). This role will focus on designing POC’s & prototypes, establishing architectural guardrails and integration patterns, and ensuring that solutions are feasible, secure, and extensible beyond the proof-of-concept (PoC) phase. Requirement to be in New York City in a hybrid capacity.

Responsibilities

• Design the end-to-end architecture for Agentic AI use cases, ensuring alignment with enterprise goals and platform capabilities as defined by the CREATe process.
• Develop the agent operating model, including decision-making frameworks, interaction protocols, and lifecycle management.
• Define and implement architectural patterns that enable scalability, security, and extensibility for AI-driven solutions.
• Collaborate with engineering teams to ensure the architecture is actionable and meets performance, reliability, and compliance requirements.
• Define architectural guardrails to ensure consistency, security, and adherence to platform standards.
• Develop integration patterns for seamless interaction between Agentic AI solutions, enterprise systems, and external services.
• Ensure all designs incorporate best practices for security, data privacy, and governance.
• Proactively identify and mitigate architectural risks, ensuring solutions are robust and resilient.
• Evaluate the feasibility of proposed solutions, ensuring they are technically achievable within project constraints.
• Design architectures that are secure by design, addressing data protection, identity management, and compliance requirements.
• Ensure solutions are extensible beyond the proof-of-concept phase, enabling future enhancements and scaling for broader use cases.
• Conduct technical reviews and validations to ensure the architecture aligns with business objectives and technical standards.
• Partner with product managers, data scientists, engineers, and business stakeholders to align on requirements and solution designs.
• Act as a trusted advisor to stakeholders, providing guidance on architectural decisions and trade-offs.
• Facilitate workshops and design sessions to gather requirements, validate designs, and drive consensus.
• Provide technical leadership and mentorship to engineering teams during implementation.

Requirements

• Google Cloud Platform (GCP): Strong experience with GCP services, including Vertex AI, BigQuery, Cloud Functions, Kubernetes Engine, and Pub/Sub.
• AI/ML Architecture: Deep understanding of AI/ML systems, including agent-based models, reinforcement learning, and adaptive decision-making.
• Agentic Patterns & Frameworks: Hands-on experience with common agentic design patterns such as RAG, orchestrator–worker, planner–executor, and collaborative multi-agent architectures.
• Agent Communication & Protocols: Proficient in MCP (Model Context Protocol) and A2A (agent-to-agent) standards for interoperable, distributed agent systems.
• Solution Architecture: Proven experience in designing scalable, secure, and extensible solutions for enterprise environments.
• Integration Patterns: Expertise in API design, microservices, and event-driven architectures.
• Security & Compliance: Knowledge of cloud security best practices, data privacy regulations, and governance frameworks.
• Programming: Strong proficiency in Python; working knowledge of Java and Go for agent services, tooling, and orchestration.
• Strong ability to create high-quality architectural diagrams, technical specifications, and documentation.
• Experience in translating business requirements into technical solutions and ensuring alignment with enterprise standards.
• Familiarity with Agile methodologies and iterative solution delivery.
• Excellent communication and stakeholder management skills, with the ability to explain complex technical concepts to non-technical audiences.
• Experience working with cross-functional teams, including product managers, engineers, and business leaders.
• Strong problem-solving skills and the ability to navigate ambiguity and complexity.

Nice-to-haves

• Google Cloud certifications (e.g., Professional Cloud Architect, Professional Machine Learning Engineer).
• Experience designing and implementing agent-based systems in a production environment.
• Familiarity with MLOps practices and tools for managing the AI/ML lifecycle.
• Knowledge of ethical AI principles and frameworks.
• Experience in scaling proof-of-concept solutions to production-grade systems.

Benefits

• Employees (and their families) are covered by medical, dental, vision, and basic life insurance.
• Employees are able to enroll in our company’s 401k plan, purchase shares from our employee stock ownership program and be eligible to receive annual bonuses.
• Employees will also receive unlimited flexible time off and ten paid holidays throughout the calendar year.
• Eligibility for ten weeks of paid parental leave will also be available upon hire date.

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