Principal Architect - Data & AI
About Us
Since 1989, SHI International Corp. has helped organizations change the world through technology. We’ve grown every year since, and today we’re proud to be a $16 billion global provider of IT solutions and services.
Over 17,000 organizations worldwide rely on SHI’s concierge approach to help them solve what’s next. But the heartbeat of SHI is our employees – all 7,000 of them. If you join our team, you’ll enjoy:
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Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S.
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Continuous professional growth and leadership opportunities.
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Health, wellness, and financial benefits to offer peace of mind to you and your family.
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World-class facilities and the technology you need to thrive – in our offices or yours.
Job Summary
The Principal Architect works across data engineering, data visualization, data governance, and AI rather than within a single technical area. On large, multi-disciplinary engagements, this role orchestrates a unified technical approach across technical area leads, each of whom owns depth within their own discipline. Alongside that delivery leadership, this role carries the practice maturation agenda: the delivery standards, accelerators, engineering practices, evaluation rubrics, and advisory frameworks that make delivery consistent and repeatable as the practice scales. The Principal Architect may be billable on engagements where specific technical depth or cross-discipline technical leadership is required. Role Description
Cross-Practice Delivery Leadership
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Lead the technical delivery approach on large, multi-disciplinary engagements spanning data engineering, data visualization, data governance, and AI.
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Orchestrate a unified solution approach across capability leads, integrating each discipline’s technical direction into one coherent delivery plan with clear sequencing, dependencies, and shared standards.
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Own delivery approach rather than solution design within any single discipline: how the work is structured, sequenced, staffed, and de-risked, and where the technical decision points sit.
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Identifydelivery risk early and intervene onengagementsdrifting on approach, quality, or coherence across workstreams.
Practice Maturation
Priorities are set with the Practice Manager, each carried from assessment through to an adopted standard.
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Delivery Excellence: baseline delivery standards, reusable accelerators and templates, engineering practices informed by DORA capabilities, and adaptive delivery approaches that balance program predictability with the experimentationrequired bydata and AIprojects.
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Talent and Engagement Model: technical interview standards and calibration, a consistent hiring bar, skills inventory and workforce visibility, and engagement health practices that protect consultant focus.
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Scoping and Advisory Excellence: structured recommendation frameworks, strategic opportunity framing that translates vague asks into clarified business problems, and clearer engagement pathways between delivery, presales, and the PMO.
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Data and AI Fluency: capability assessment, targeted learning pathways mapped to assessment outcomes and to the pace of Microsoft platform change, and improved use of internal data for practice decision-making.
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Build capabilities so they outlast the person driving them, with documented standards, named owners, and adoption evidence.
AI-Accelerated Delivery
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Apply AI tooling and agentic patterns to how the practice deliversvalue, improving the speed, consistency, and quality of consulting workacross all engagements.
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Evaluate where AI meaningfully changes delivery economics and where it introduces review overhead without netgain andbuild the evidence to distinguish the two.
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Fold proven patterns into delivery standards and accelerators so that gains are structural to the practice rather than dependent on individualhabit.
Practice Leadership and Capabilit