Senior Computational Designer

Key Responsibilities

• Apply computational design methods to mission critical, data center, industrial, advanced manufacturing, and other technically complex building projects.
• Develop parametric and data-driven workflows that connect geometry, program, planning criteria, engineering inputs, equipment layouts, system requirements, performance criteria, and documentation outputs.
• Support early design exploration, option studies, layout evaluation, and decision-making through practical computational methods.
• Work across architecture, electrical, mechanical, structural, and digital delivery teams to improve coordination, reduce manual rework, and increase design clarity.
• Translate project-specific challenges into reusable workflows, automation patterns, and delivery methods that can be applied across future projects and sectors.
• Lead practitioner and project-team conversations to identify high-value automation opportunities.
• Build Revit-based automations using Dynamo, Rhino.Inside.Revit, Speckle, the Revit API, or related workflows, with a focus on electrical and mechanical design, coordination, documentation, and data tasks.
• Automate repetitive design, analysis, QA/QC, documentation, modeling, and data-management tasks where they improve speed, reliability, or coordination across disciplines.
• Build, test, validate, and document proofs of concept against real project needs and conditions.
• Partner with development and platform teams to transition successful prototypes into scalable BIM-integrated tools or supported firmwide workflows.
• Balance innovation with reliability by ensuring automations are maintainable, aligned with project delivery standards, and ready for handoff when appropriate.

Specialist Support for Data Centers and Industrial Projects

• Support planning, test-fit, modularization, spatial coordination, MEP systems coordination, equipment layouts, and repeatable documentation workflows for high-complexity technical projects.
• Structure project data so teams can make faster, clearer decisions across disciplines and phases.
• Evaluate tradeoffs related to layout, coordination, performance, delivery speed, and constructability.
• Identify opportunities to standardize computational workflows across recurring project types, building systems, and client delivery requirements.
• Support workflow scoping, internal training, and hands-on implementation for teams adopting computational methods.

Value, Metrics and Communication

• Define, track, and communicate value metrics for computational design, including hours saved, reduced rework, faster iteration, improved coordination, risk reduction, delivery quality, workflow reuse, project-team adoption, and demonstrated business value.
• Translate technical work into clear project and business language for project managers, discipline leads, clients, and firm leadership.
• Provide regular reporting on active automations, utilization, project impact, adoption barriers, lessons learned, and opportunities for broader deployment.
• Support pursuits, proposals, and internal case studies by showing how automation and computational design improve delivery for mission critical and other technical sectors.