Director of AI and Enterprise Architecture

Role overview Lead the technical architecture of client projects that bring AI agents into complex enterprise environments. You will map each organization’s systems, turn business workflows into clear technical requirements, and guide embedded engineers as they move solutions from pilot into production. This is a client-facing consulting role focused on secure, governed delivery.

Responsibilities - Set technical direction for engagements and guide engineers building alongside client teams. - Map enterprise platforms, custom applications, data stores and integrations so delivery teams understand the environment. - Work with process owners to define workflow steps, data, decisions, permissions and human approval points for agents. - Design connections to systems of record using APIs, integration platforms, event streams, agent protocols and suitable data access patterns. - Guide deployment through testing, release controls, monitoring and operational handoff. - Define agent identity, access, audit and governance controls, and secure approval from security and risk stakeholders. - Advise senior client technology leaders and turn engagement experience into reusable architecture patterns and playbooks.

Requirements - 7–10 years in enterprise or solution architecture, or technical leadership in complex enterprise software environments. - Hands-on expertise with at least two major enterprise platforms, including their data models, APIs, extension approaches and upgrade constraints. - Strong enterprise integration knowledge, including REST or SOAP APIs, middleware or iPaaS, event-driven architecture and master data management. - Production experience with AI applications, agent workflows, RPA or intelligent automation, and sound judgment about appropriate uses. - Track record taking enterprise systems from design to production, including SDLC, change control, testing, monitoring and support. - Knowledge of identity and access management, SSO, OAuth, role-based access, auditing and regulatory obligations; client-facing consulting experience is required.

Nice to have Experience with architecture frameworks or platform certifications; agent frameworks and protocols, retrieval-augmented generation or agent evaluation; cloud and modern data platforms; embedded engineering delivery; regulated industries; or published enterprise AI work.

Benefits and work setup Remote role serving clients in the western United States; Pacific or Mountain time is preferred. Success includes billable delivery, production adoption, client trust and reusable practices.