AI Platform Architect - New York

Overview: Our client is a fortune 500 company in the financial services undergoing a significant AI transformation initiative. They are building a strategic AI platform designed to support intelligent applications, automation capabilities, copilots, and agentic workflows across multiple business units. The platform is already operating in production and is entering its next phase of growth, with a strong focus on scalability, resiliency, security, governance, and enterprise adoption. This role is suited to a senior architect who enjoys solving complex platform challenges and defining standards that enable teams across the organization to build and operate AI solutions safely and at scale. Based in New York, with 3 days in office.

Key Responsibilities: Define and evolve the enterprise AI platform architecture, ensuring it can support current and future AI capabilities across the organization. Establish architecture standards covering model access and routing, AI and API gateways, agent frameworks, MCP integration, tool execution patterns, retrieval and RAG services, multi-agent orchestration, runtime controls, governance frameworks, and platform interoperability. Lead capacity planning activities across compute, containers, databases, vector stores, inference services, model-serving infrastructure, and other critical platform components. Design highly available, fault-tolerant solutions with a focus on resiliency, disaster recovery, graceful degradation, failover strategies, and production readiness. Partner closely with engineering, cloud, infrastructure, security, and DevOps teams to ensure platform reliability, performance, and operational excellence. Define standards for observability, monitoring, telemetry, tracing, auditing, alerting, and AI-specific performance measurement across distributed AI workloads. Review new AI use cases and ensure alignment with approved platform patterns, security controls, governance requirements, and architectural standards. Drive platform modernization initiatives and identify opportunities to improve scalability, performance, reliability, governance, and developer experience. Required

Qualifications: 7+ years of experience in enterprise architecture, platform engineering, distributed systems, or cloud architecture. Proven experience designing and operating large-scale enterprise platforms rather than individual applications. Strong understanding of scalability, capacity management, high availability, resiliency engineering, fault tolerance, and security architecture. Hands-on experience with GenAI technologies including agent frameworks, LLM orchestration, RAG, vector retrieval, tool calling, AI evaluation frameworks, observability, and governance patterns. Experience establishing technical standards, reference architectures, and engineering best practices adopted across multiple teams and products. Strong communication and stakeholder management skills with the ability to influence senior technical and business leaders. Preferred

Qualifications: Experience working within large, highly regulated enterprise environments. Experience designing and supporting shared AI platforms used by multiple teams, products, or business units. Familiarity with multi-agent systems, AI gateways, model lifecycle management, platform observability, runtime controls, evaluation frameworks, and enterprise AI governance models. Experience supporting production environments requiring strict uptime, security, resiliency, and operational controls.