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Solution Architect - Enterprise Systems

Job in Midvale, Salt Lake County, Utah, 84047, USA
Listing for: ZAGG
Full Time position
Listed on 2026-07-10
Job specializations:
  • Software Development
Salary/Wage Range or Industry Benchmark: 140000 - 200000 USD Yearly USD 140000.00 200000.00 YEAR
Job Description & How to Apply Below

Location: Midvale, UT

Remote Status: On‑Site

Job :528

# of Openings:1

ZAGG is a global leader in mobile accessories, driving innovation in device protection, power, and productivity through its ZAGG and mophie product lines. With operations in the US, Ireland and China, ZAGG’s products are available worldwide at leading retailers. Committed to sustainability, ZAGG is taking steps to reduce its carbon impact in manufacturing, packaging, materials, shipping, and recycling. Our mission is to protect and enhance your mobile lifestyle while making a positive impact on the planet.

As ZAGG’s Solution Architect -- Enterprise Systems
, you will be the strategic and technical authority connecting ZAGG's business goals to our enterprise technology landscape. You will design scalable, intelligent system architectures, lead complex cross‑functional programmes, and ensure every solution is purpose‑built to deliver measurable business outcomes — balancing speed‑to‑market with long‑term engineering rigour.

What You Will Do

Business Alignment & Strategic Planning

  • Partner with executive, product, and commercial leadership to translate business objectives into architecture decisions with clear, measurable outcomes.
  • Lead discovery workshops and requirements sessions, producing BRDs and Solution Design Documents that connect every technical decision to a KPI, OKR, or business capability gap.
  • Build and present multi‑year technology roadmaps tobusinessstakeholders, articulating investment rationale, risk trade‑offs, and expected ROI.
  • Identify where intelligent automation and machine learning capabilities caneliminateoperational friction, accelerate revenue, or unlock new business capabilities — and build the business case to pursue them.
  • Facilitateprioritizationworkshops (MoSCoW, RICE, WSJF) to align stakeholders on scope, sequencing, and return on investment across competing initiatives.
  • Contribute to vendor evaluations and RFPs, assessing enterprise platforms and emerging technology services against business requirements, scalability, and total cost of ownership.
  • Design end‑to‑end architectures across commerce, ERP, CRM, OMS, PIM, supply chain, and data platforms — incorporating intelligent and automated capabilities as core components rather than afterthoughts.
  • Define the intelligent platform layer within the enterprise architecture: the foundational models, data pipelines, orchestration patterns, and API contracts that power data‑driven and automated capabilities across the business.
  • Architect solutionsleveraginglarge language models and generative capabilities — including retrieval‑augmented pipelines and agentic workflows — connected to enterprise systems via governed, versioned APIs.
  • Lead build vs. buy evaluations for enterprise systems and intelligent capabilities, assessing vendor platforms, foundation models, and custom development against businessneedand long‑term maintainability.
  • Define non‑functional requirements across the full stack:availabilitySLAs, disaster recovery targets (RTO/RPO), security posture, model performance baselines, and compliance obligations (GDPR, CCPA, SOX, EU AI Act).
  • Produce and maintain

    Architecture Decision Records (ADRs), capability maps, system‑of‑record designations, and architectural diagrams as the authoritative source of truth.
  • Architect enterprise integrations using scalable middleware and iPaaS platforms (Mule Soft& other platforms) and event‑driven messaging(AWS,SQS) —extended to support intelligent data ingestion, model feedback loops, and real‑time inference.
  • Define the data strategyrequiredto power intelligent capabilities: feature stores, vectordatabasesreal‑time streaming pipelines, andlakehousearchitecture (Snowflake, Databricks,Big Query).
  • Establish master data management and data governance standards ensuring all systems — including those powering automated and predictive capabilities — are built on accurate, consistent, and trustworthy data.
  • Own API strategy across enterprise systems and intelligent services: versioning standards, lifecycle management, security controls (OAuth 2.0,mTLS), and developer experience including interfaces for language model and agent‑to‑system…
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