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Ai Alignment Jobs in Iowa (NOW HIRING)

... align cross functional stakeholders • Excellent business acumen and fluent in linking data ... AI platforms (Azure, GCP, Databricks, Snowflake, etc.) • Excellent conceptual, analytical ...

Drive enterprise AI strategy, governance, and adoption while empowering teams across the ... align people, process, and technology in support of strategic goals. Lead through influence and ...

Drive enterprise AI strategy, governance, and adoption while empowering teams across the ... align people, process, and technology in support of strategic goals. Lead through influence and ...

$62.25 - $85/hr

... aligned with enterprise architecture principles, leveraging SAP BTP services and SAP AI capabilities (SAP AI Core, SAP AI Launchpad, SAP Generative AI, SAP Joule Studio, etc.) • Document AI use ...

LCS is looking for a visionary VP of Data & AI to lead the organization's transformation to ... Clear executive presence and ability to influence and align cross functional stakeholders.

LCS is looking for a visionary VP of Data & AI to lead the organization's transformation to ... Clear executive presence and ability to influence and align cross functional stakeholders.

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Ai Alignment information

What is AI alignment?

AI alignment refers to the process of ensuring that artificial intelligence systems act in ways that are aligned with human values, intentions, and ethical standards. This field focuses on designing AI models that not only achieve their objectives but also do so safely and beneficially for humanity. As AI systems become more advanced, alignment becomes increasingly important to prevent unintended consequences or harmful behaviors. Researchers in AI alignment work on technical solutions, such as value learning and interpretability, as well as broader ethical and policy considerations.

What is the difference between Ai Alignment vs Data Scientist?

AspectAi AlignmentData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or related fieldsDegree in Data Science, Statistics, Computer Science, or related fields
Work EnvironmentResearch labs, AI development companies, tech firmsTech companies, finance, healthcare, consulting firms
Industry UsageFocuses on ensuring AI systems behave as intendedAnalyzes data to extract insights and build predictive models

While both roles involve advanced technical skills, Ai Alignment specialists focus on aligning AI systems with human values and safety, whereas Data Scientists analyze data to inform business decisions. The roles often overlap in AI research environments but serve different primary objectives.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI product executive, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact. Such salaries are common in top tech companies or specialized AI firms for senior or executive-level professionals.

How to become an AI alignment researcher?

To become an AI alignment researcher, typically a strong background in computer science, machine learning, or related fields is required, often including advanced degrees such as a master's or Ph.D. in these areas. Developing expertise in AI safety, ethics, and formal verification, along with programming skills in Python and familiarity with AI frameworks, is essential. Gaining research experience through academic projects, internships, or contributing to open-source initiatives can also be valuable for entering this specialized field.

What are some common challenges faced by professionals working in AI alignment roles?

Professionals in AI alignment roles often encounter the challenge of translating complex ethical principles and human values into machine-understandable objectives. Balancing technical constraints with theoretical considerations requires close collaboration with cross-functional teams, including ethicists, engineers, and product managers. Additionally, the rapidly evolving landscape of artificial intelligence demands continuous learning to stay current with new alignment techniques and research findings. Navigating these challenges can be intellectually stimulating and offers significant opportunities for interdisciplinary growth.

What are the key skills and qualifications needed to thrive as an AI Alignment Specialist, and why are they important?

To thrive as an AI Alignment Specialist, you need a strong background in computer science, mathematics, and machine learning, often evidenced by an advanced degree in a related field. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and formal verification systems is typically required, along with understanding of AI safety principles. Analytical thinking, ethical reasoning, and effective communication are crucial soft skills for success in this role. These skills ensure that AI systems are developed safely, ethically, and in alignment with human values, which is essential for mitigating risks associated with advanced AI.

Which 3 jobs will survive AI?

AI alignment professionals, software engineers specializing in AI safety, and ethicists focused on AI governance are likely to continue being in demand as AI technology advances. These roles require specialized knowledge, critical thinking, and oversight skills that are difficult to automate. Continuous learning and expertise in AI tools and ethical frameworks are essential for these jobs to remain relevant.

What is an AI alignment?

AI alignment in the context of AI safety and ethics refers to designing and developing artificial intelligence systems so that their behaviors and outcomes align with human values and intentions. AI alignment specialists work to ensure that AI systems act reliably and safely, often using techniques like value specification, interpretability, and robustness testing. This field requires skills in machine learning, ethics, and programming, and is critical for creating beneficial and trustworthy AI systems.
What are popular job titles related to Ai Alignment jobs in Iowa? For Ai Alignment jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Ai Alignment jobs in Iowa look for? The top searched job categories for Ai Alignment jobs in Iowa are:
What cities in Iowa are hiring for Ai Alignment jobs? Cities in Iowa with the most Ai Alignment job openings:
Infographic showing various Ai Alignment job openings in Iowa as of July 2026, with employment types broken down into 79% Full Time, 14% Part Time, and 7% Contract. Highlights an 74% In-person, and 26% Remote job distribution.

AI & Automation Solution Architect- Hybrid Des Moines, Iowa

American Enterprise Mutual Holding

Des Moines, IA • On-site

Full-time

Medical, Retirement, PTO

Posted 17 days ago


Job description

Wellabe is hiring for an AI & Automation Solution Architect. This role supports the AI & Automation Center of Excellence by designing reusable, secure, and scalable solution patterns for AI and automation capabilities. This role builds reference implementations, validates tools and approaches, provides technical advisory support, and helps distributed teams design solutions aligned with enterprise architecture, security, governance, and responsible AI expectations. The role enables a federated delivery model where business and technology teams retain ownership while the CoE provides patterns, standards, reusable assets, and acceleration.

Core 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 hands-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 AI-specific risks, production readiness needs, human-in-the-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 business-facing playbooks, and continuously improved based on implementation lessons.
  • Support Lifecycle Execution from Intake to Scale
    • Support the end-to-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 pilot-to-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 CoE-provided guidance and reusable assets.
    • Provide technical enablement through demos, design walkthroughs, knowledge-sharing sessions, office hours, and communities of practice.
    • Help teams determine when to use generative AI, workflow automation, RPA, low-code/no-code tools, APIs, data services, or traditional application capabilities while promoting reuse over one-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 hands-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.
Education
  • Bachelor’s degree in information technology, computer science, engineering, data/analytics, business systems, or a related field; equivalent work experience will also be considered.
  • Additional coursework with emphasis in AI, automation, data/analytics, digital business solutions, systems integration, or enterprise technology preferred.
Benefits
  • Hybrid availability
  • 401(k) with company match
  • Health insurance
  • Paid time off, holidays
  • Volunteer time off
  • Lifestyle Spending Account (LSA)
  • Paternity leave
Growth opportunities

We believe each of us has potential to grow and adapt with our business. We take your career as seriously as you do. Helping you develop your skills and talents leads to opportunities — not only for you, but also for our company. That’s why we provide:

  • LinkedIn Learning Premium access
  • CliftonStrengths® assessment and coaching
  • On-site and virtual workshops and cohorts featuring world-class content from FranklinCovey, Crucial Learning, Gallup, and more 
  • Free world-class insurance acumen courses through AHIP and LOMA
  • Reimbursement and bonus opportunities for professional designations and certifications, including a tuition reimbursement program 
  • Opportunities to take part in Wellabe's mentorship programs 
About Wellabe

Since 1929, Wellabe has been finding solutions to help our customers protect their health and financial well-being. And we’re committed to fostering an internal culture of inclusivity, well-being, and development so each of our team members can succeed. Learn more about Wellabe’s culture of betterment by visiting wellabe.com/culture.

Wellabe is full of smart, caring, hard-working people with a broad range of talents who understand collaboration is key. We bring our best selves every day, to connect with others to solve problems, spark innovation, and bring ideas to life. Meet the team and learn what makes Wellabe a great place to work by visiting wellabe.com/news/employee-spotlights.

Our core values:

  • Be dedicated: Show unwavering commitment by proactively taking initiative, setting clear goals, and managing time effectively.
  • Be trustworthy: Take accountability for actions, navigate difficult conversations with integrity, and build strong relationships through consistent, honest behavior.
  • Be determined: Demonstrate enthusiasm and a relentless drive to overcome obstacles and achieve goals.
  • Be collaborative: Foster teamwork by being self-aware, actively listening, and effectively communicating across all levels.
  • Be open: Embrace diversity and new ideas to create an inclusive environment.
  • Be generous: Embody generosity and compassion by serving a greater purpose and helping others.
  • Be better: Commit to continuous improvement and adapt effectively to change.
  • Be well: Prioritize physical and mental health, manage stress, and demonstrate emotional intelligence.