Architect

As our Architect, you will be the technical authority for one or more core product lines, owning the end‑to‑end architecture and ensuring alignment with Accruent’s platform strategy. You will design scalable, secure, and AI-enabled product architectures that support both our core SaaS offerings and emerging AI-driven capabilities. You will operate at the intersection of product engineering, platform services (APIM, Identity, Data, AI), and business strategy, partnering closely with Engineering, Product Management, Data & AI teams, and TechOps to set standards, guide implementation, and drive execution. Key Responsibilities * Product Architecture & Strategy * Define and own the architecture vision, standards, and roadmap for assigned products or product lines * Design scalable, high-performance, and resilient systems across application, integration, data, and AI layers * Establish and maintain current-state and future-state architecture documentation * Align product architecture with business priorities, customer needs, and platform strategy (Identity, APIM, Data, AI) * AI & Data Platform Enablement * Architect product capabilities that leverage AI/ML and GenAI services, including: * AI-assisted workflows and decisioning * Agent integrations and agent-driven experiences * Data-driven insights and predictive capabilities * Partner with Data & AI teams to ensure: * Data pipelines, models, and services are scalable, secure, and production-ready * AI capabilities are integrated into products in a consistent and reusable manner * Define architecture patterns for: * Model integration (APIs, event-driven, batch/real-time) * Data access and governance * AI service orchestration within product workflows * Platform Integration & Standardization * Ensure consistent adoption of shared platform capabilities, including: * API Management (APIM) * Identity and access management (Auth0) * Data and integration platforms * AI/ML services and shared AI infrastructure * Translate platform capabilities into practical, product-level implementations * Identify platform gaps and help evolve reusable patterns and “paved roads” * Responsible AI, Security & Governance * Contribute guardrails for responsible AI usage, including: * Data privacy and residency * Access control and identity propagation * Model usage governance and auditability * Partner with Security and Data teams to ensure compliance with: * Enterprise security standards * Data governance requirements * Contribute to architecture governance, including design reviews and ADRs * Delivery Engagement & Technical Leadership * Embed with engineering teams to co-design solutions for key initiatives and roadmap delivery * Lead architecture reviews, design sessions, and tradeoff discussions * Ensure decisions are intentional, documented, and aligned across teams * Balance speed vs quality, enabling rapid delivery without compromising architecture integrity * Engineering Collaboration & Enablement * Partner with Engineering, SRE, Ops, and Data teams on roadmap execution and delivery practices * Provide hands-on architectural guidance and mentorship to engineers and tech leads * Promote reusable patterns, standards, and developer-friendly approaches * Enable teams to integrate platform and AI capabilities with minimal friction * Technical Debt, Risk & Scalability * Identify and mitigate: * Architectural risks * Performance and scalability concerns * AI and data-related risks (model performance, data drift, integration complexity) * Own product-level technical debt strategy and prioritization * Drive proactive architecture evolution rather than reactive fixes * Cross-Product Alignment & Integration * Ensure product architecture supports cross-product workflows and shared capabilities * Promote consistency across: * APIs * Data models * AI integrations and services * Contribute to a unified architecture vision...