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Assistant Governance Risk Compliance Jobs in Iowa

Drive stakeholder communication, governance, and decision-making. * Ensure compliance with project ... Expertise in project planning, governance, risk management, and change management. * Experience ...

Director of Audit Services

Iowa, IA ยท On-site

$102K - $128K/yr

ViClarity is a leading global provider of Governance, Risk, and Compliance (GRC) software, serving clients across highly regulated Financial Services and Healthcare sectors. Our award-winning ...

Compliance Program Advisor

Glenwood, IA ยท On-site

$70K - $156K/yr

Escalates issues through proper governance channels as needed, and recommends corrective action ... Managing Risk - Assessing and effectively managing all of the risks associated with their business ...

... of governance, risk management and internal controls over financial reporting. In this position ... Work with external auditors to ensure Sarbanes-Oxley (SOX) compliance. * Work to develop new ...

... of governance, risk management and internal controls over financial reporting. In this position ... Work with external auditors to ensure Sarbanes-Oxley (SOX) compliance. * Work to develop new ...

Showing results 21-40

Assistant Governance Risk Compliance information

What is the difference between Assistant Governance Risk Compliance vs Compliance Analyst?

AspectAssistant Governance Risk ComplianceCompliance Analyst
CertificationsCertifications like CCEP, CRCM, or ISO often preferredSimilar certifications such as CCEP, CRCM, or ISO
Work EnvironmentCorporate, regulated industries, compliance departmentsCorporate, financial, healthcare, or manufacturing sectors
Employer & Industry UsageUsed in organizations with governance, risk, and compliance functionsCommon in compliance departments focusing on regulatory adherence
Search & Comparison IntentOften compared for entry-level or supporting compliance rolesCompared for analytical and regulatory compliance positions

The main difference is that an Assistant Governance Risk Compliance supports broader governance and risk functions, while a Compliance Analyst focuses more on analyzing and ensuring adherence to specific regulations. Both roles require similar certifications and are found in regulated industries, but their focus areas and responsibilities differ slightly.

What are the most commonly searched types of Governance Risk Compliance jobs in Iowa? The most popular types of Governance Risk Compliance jobs in Iowa are:
What are popular job titles related to Assistant Governance Risk Compliance jobs in Iowa? For Assistant Governance Risk Compliance jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Assistant Governance Risk Compliance jobs in Iowa look for? The top searched job categories for Assistant Governance Risk Compliance jobs in Iowa are:
What cities in Iowa are hiring for Assistant Governance Risk Compliance jobs? Cities in Iowa with the most Assistant Governance Risk Compliance job openings:

AI & Automation Solution Architect

Jobtailor

Des Moines, IA โ€ข On-site

$120 - $170/hr

Other

Posted 3 days ago

New


Job description

Responsibilities
  • Design AI and Automation Solution Patterns
    • Develop reusable AI and automation solution patterns that translate business use cases into practical conceptual, logical, and technical designs.
    • Define repeatable design approaches, documentation standards, testing expectations, support considerations, and measurement practices that can be adopted across business and technology teams.
    • Partner with enterprise architecture to ensure solution patterns align with enterprise standards, integration principles, security expectations, and cloud architecture direction.
  • Build Reference Implementations and Proofs of Value
    • Build or co-build prototypes, proof-of-value implementations, reusable components, and demonstration scenarios that validate AI and automation approaches.
    • Evaluate emerging tools, platforms, integration patterns, automation capabilities, and technical assumptions through handsโ€‘on reference implementations.
    • Document implementation lessons, constraints, and recommended patterns so solutions can be replicated, adapted, extended, and moved toward production.
  • Provide Technical Advisory and Design Support
    • Serve as a technical advisor to business, product, process improvement, and technology delivery teams pursuing AI and automation opportunities.
    • Translate use cases, workflow impacts, business requirements, and adoption needs into practical solution options in partnership with the AI & Automation Enablement Lead.
    • Guide teams through tool selection, architecture, integration, data, security, controls, testing, deployment, scaling considerations, and technical risk tradeoffs.
  • Support Responsible AI and Automation Practices
    • Embed responsible AI and automation practices into solution design, including transparency, human oversight, data protection, security, privacy, explainability where appropriate, and appropriate use limitations.
    • Partner with governance, risk, compliance, legal, privacy, information security, and data governance teams to ensure solutions follow enterprise guardrails.
    • Identify, document, and support mitigation of AIโ€‘specific risks, production readiness needs, humanโ€‘inโ€‘theโ€‘loop controls, operational monitoring, and auditability requirements.
  • Define Technical Standards, Templates, and Reusable Assets
    • Create and maintain technical templates, reference architectures, design checklists, prompt engineering patterns, automation standards, testing guides, and production readiness materials.
    • Develop reusable components, scripts, connectors, workflow patterns, prompt libraries, configuration examples, and technical accelerators where appropriate.
    • Partner with CoE leadership to ensure technical assets are understandable, reusable, aligned with businessโ€‘facing playbooks, and continuously improved based on implementation lessons.
  • Support Lifecycle Execution from Intake to Scale
    • Support the endโ€‘toโ€‘end AI and automation lifecycle, from opportunity assessment and solution design through prototype development, governance alignment, testing, deployment readiness, adoption, measurement, and scale.
    • Define production readiness expectations for technical design, documentation, ownership, monitoring, support model, controls, adoption needs, and benefit tracking.
    • Partner with delivery teams to plan pilotโ€‘toโ€‘production transitions, resolve technical barriers, and ensure solutions are secure, supportable, observable, maintainable, and aligned with enterprise architecture expectations.
  • Enable Distributed Delivery Teams
    • Coach technology and business teams on approved AI and automation patterns, tools, standards, delivery practices, and responsible use of CoEโ€‘provided guidance and reusable assets.
    • Provide technical enablement through demos, design walkthroughs, knowledgeโ€‘sharing sessions, office hours, and communities of practice.
    • Help teams determine when to use generative AI, workflow automation, RPA, lowโ€‘code/noโ€‘code tools, APIs, data services, or traditional application capabilities while promoting reuse over oneโ€‘off solutions.
  • Partner Across Platforms, Data, Architecture, and Security
    • Collaborate with enterprise architecture, cloud/platform teams, data and analytics, application teams, security, identity/access management, infrastructure, and operations.
    • Ensure solutions consider data readiness, integration needs, access controls, platform constraints, system performance, monitoring, operational support, scalability, and vendor/platform limitations.
    • Support alignment with approved platforms, enterprise technical standards, capability roadmaps, and technical enablement needs.
Qualifications
  • 5+ years of experience in solution architecture, application development, automation engineering, systems integration, enterprise applications, digital transformation, or a related technology field required.
  • Experience designing and delivering AI, automation, workflow, low-code/no-code, data-enabled, or digital business solutions using enterprise applications, APIs, integrations, and data services required.
  • Experience with Microsoft cloud, AI, automation, and low-code/no-code platforms; responsible AI, AI governance, data privacy, information security, model risk, vendor risk, regulatory, or compliance considerations; and regulated industry environments such as insurance, financial services, or healthcare strongly preferred.
  • Familiarity with advanced AI and automation practices, including MLOps, LLMOps, prompt engineering, retrieval-augmented generation, document intelligence, process mining, workflow orchestration, knowledge management, or API-based integrations preferred.
  • Experience developing prototypes, proofs of value, reusable technical assets, reference architectures, enterprise solution patterns, or supporting design reviews, architecture governance, agile delivery, product management, design thinking, Lean, Six Sigma, DevOps, continuous improvement, communities of practice, or technical training preferred.
  • Strong knowledge of solution design, systems integration, security-by-design, testing, documentation, production readiness, supportability, operational handoff, and translating business needs into practical solution options.
  • Strong collaboration, problem-solving, facilitation, consulting, documentation, stakeholder management, and communication skills, with experience working across business, product, architecture, security, data, compliance, risk, and technology teams.
  • Knowledge of solution architecture, systems integration, AI and automation technologies, responsible AI practices, governance, security, production readiness, and operational support considerations.
  • Translate business needs into practical AI, automation, workflow, and digital solution designs aligned with enterprise standards.
  • Develop reusable solution patterns, prototypes, technical templates, reference architectures, and other enablement assets that support repeatable delivery.
  • Evaluate tools, platforms, integration patterns, and automation capabilities through handsโ€‘on experimentation and documented lessons learned.
  • Advise, coach, and enable business and technology teams on approved AI and automation practices, responsible use, and pilot-to-production execution.
  • Partner across architecture, data, security, compliance, risk, governance, operations, and delivery teams to ensure solutions are secure, scalable, supportable, and aligned with enterprise expectations.
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