AI Architect / Technical Lead

About the role

RRD provides marketing, packaging, print, and business services to the world’s most respected brands. The company’s proprietary technology, advanced data analytics, and expertise fuel organizational decision‑making from strategy through execution, delivering sustainable solutions with the lowest possible environmental impact. Global organizations and regulated industries trust RRD to reduce complexity and drive audience connections across the entire customer journey.

Join Williams Lea, an RRD Company, in transforming legal and business support through AiVA—our proprietary AI orchestration platform. Working in high‑energy, bootcamp‑style pods directly alongside top global law firms, our teams rapidly design, test, and deploy cutting‑edge AI workflows that power business‑critical operations. If you thrive on fast‑paced iteration and want to redefine the future of professional services, apply today to join our AiVA Talent Pipeline and shape next‑generation AI solutions.

The Technical Lead is the senior architect and technical role in AiVA engagements. Once a client engagement is signed, this role owns the architectural pattern, the integration approach, and the technical quality of everything the AiVA pod builds. The role provides architectural direction, technical review, and escalation resolution. Accountable not for building skills but for the technical soundness of what gets built and liaising with the platform engineering team where necessary. Overall aims include technical architecture that supports engagement outcomes (scalable, maintainable, secure, defensible under client technical scrutiny), consistent architectural pattern across assigned pods, sound technical decisions with clear architectural guidance to AI Workflow Engineers, technical soundness that supports both immediate engagement outcomes and long‑term client platform investment, and architectural clarity that lets AI Workflow Engineers build at pace without technical rework.

Responsibilities

• Define the architectural pattern for each engagement: skill decomposition, tool orchestration, data flow, integration approach, and deployment model.
• Ensure all architecture patterns are in line with security best practices and with client requirements.
• Design client‑specific guardrails as appropriate.
• Review and sign off on AI Workflow Engineer builds against the agreed architectural pattern.
• Own integration architecture with client systems: authentication, data ingress, downstream deployment, and monitoring.
• Make platform‑versus‑custom decisions with the Head of Platform Engineering and Product where the engagement stretches platform capability.
• Design and document the target technical state, transition plan, and operational readiness criteria for hando