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. Apply tot his job