AI-Consultant / Architect

Job Summary

The AI Consultant / Architect is the senior technical authority within SoftwareOne’s AI advisory practice in North America. This role is responsible for translating AI ambition into production-grade, governed, and commercially viable architectures that can be successfully delivered at scale. 

The role defines end-to-end AI solution architecture across generative AI, agentic systems, and traditional ML, ensuring technical feasibility, cost awareness, governance, and delivery readiness. It acts as the key technical advisor to customer technology leadership, shaping solution design decisions and ensuring that architectures are defensible, scalable, and aligned with enterprise standards. 

In addition to delivery-focused architecture work, this role helps define reference architectures, technical standards, and reusable patterns that guide the evolution of the AI advisory practice. 

SoftwareOne is an AI‑forward company. We actively use AI across our business to improve productivity, decision‑making, and outcomes - and we are intentional about hiring people who are curious, hands-on, actively apply AI, and lead by example as technology continues to evolve. 

Role & Responsibilities

Architecture & solution design

• Own  end-to-end solution architecture  for AI engagements spanning deterministic automation, traditional ML, and generative / agentic AI. 

• Design for the full lifecycle — data pipelines, model selection, integration, orchestration, evaluation, and monitoring. 

• Make and document the build-vs-buy and model-selection decisions, with the trade-offs made explicit for the customer. 

Advisory & customer engagement

• Lead  AI strategy, readiness, and use-case discovery  workshops with customer business and technology leadership. 

• Produce architecture blueprints, roadmaps, and business cases that connect technical design to measurable business outcomes. 

• Give account and delivery teams a credible technical narrative that supports pipeline and protects delivery. 

Governance, risk & cost

• Embed  AI governance and risk management  into every design — aligned to NIST AI RMF, the EU AI Act, and SR 11-7 where applicable. 

• Account for cloud and inference economics (FinOps) so solutions are affordable to run, not just to build. 

• Assess and communicate blast-radius risk, data exposure, and model failure modes before they reach production. 

Enablement & technical leadership

• Mentor consultants and solution engineers, raising the  technical bar across the practice . 

• Capture patterns and lessons from each engagement so the practice compounds its expertise over time. 

Travel up to 30%  to support customer engagements, workshops, and architecture advisory sessions.