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Ai Platform Engineer Jobs in Iowa (NOW HIRING)

AWS platform engineer

West Des Moines, IA · On-site

$52 - $71.25/hr

Title : DevOps / Platform Engineer Location: West Des Moines, IA Type: Contract 4 Days On-Site ... AI-generated changes and validating them with tests or evidence. Experience with Coder, GitHub ...

... AI platforms. • Architect scalable, high-performance machine learning and GenAI solutions for NLP ... engineering, experimentation, training, validation, deployment, and monitoring. • Build large ...

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Ai Platform Engineer information

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$31

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How much do ai platform engineer jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for ai platform engineer in Iowa is $60.07, according to ZipRecruiter salary data. Most workers in this role earn between $47.40 and $69.33 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

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

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Iowa?

For Ai Platform Engineer jobs in Iowa, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in Iowa look for?

The top searched job categories for Ai Platform Engineer jobs in Iowa are:

What cities in Iowa are hiring for Ai Platform Engineer jobs?

Cities in Iowa with the most Ai Platform Engineer job openings:

Infographic showing various Ai Platform Engineer job openings in Iowa as of August 2026, with employment types broken down into 1% As Needed, 56% Full Time, 41% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $124,947 per year, or $60.1 per hour.

Staff Data and AI Platform Engineer

Ames, IA • On-site

Workiva, Inc.
Software Development • 1 - 5K employees

Other

Retirement

This job post has expired today. Applications are no longer accepted.


Key responsibilities

  • Own and operate the design, reliability, security, and cost efficiency of account-level data platform infrastructure including warehouses, RBAC, replication, governance, and platform standards.

  • Define and maintain platform standards, configure and operate Snowflake account infrastructure, and evolve data mesh boundaries across business domains.

  • Evaluate emerging technologies, shape the data platform roadmap, and make architectural decisions to support AI/ML workflows and enterprise data needs.


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz


Job description

The Staff Data and AI Platform Engineer at Workiva serves as the technical authority for the Enterprise data platform. You'll own design, reliability, security, and cost efficiency of account-level infrastructure (warehouses, RBAC, replication, governance, platform standards) while enabling domain teams to build and operate dbt Mesh projects safely at scale. You'll set technical direction, translate ambiguous challenges into clear standards and architectural decisions, and raise the engineering bar across data and analytics.

You'll proactively evaluate emerging technologies (including AI/ML data substrate integration), shape the multi-year data platform roadmap, and drive buy/build/adopt decisions with leadership. Key partnerships include GRC on FedRAMP and data-boundary controls, Atlan for enterprise cataloging, and AI/ML platform teams on AI application foundations. You'll align stakeholders across Data Engineering, Analytics Engineering, Data Science, ML Platform, AI Product, BI, Security, Data Ops, and business partners-influencing technical direction without direct authority.

Reports to: Sr Director of Enterprise Data Platform (Data & Analytics function under CIO)

What You'll Do

Platform Strategy & Technical Leadership

  • Define multi-year data platform architecture vision and roadmap; present tradeoffs and sequencing to DnA and engineering leadership

  • Serve as technical decision-maker for platform-wide architectural choices: buy/build/adopt, technology evaluation, and cross-domain standard-setting

  • Evaluate and pilot emerging data platform technologies; run POCs and develop architectural recommendations

  • Drive alignment across Data Engineering, Analytics Engineering, AI/ML Platform, Security, and Data Ops

  • Mentor data and analytics engineers; define engineering standards, review designs/PRs, and grow platform competency

Platform Engineering & Operations

  • Define and maintain Snowflake platform standards: naming conventions, schema/database layout, warehouse tiers, role hierarchy, environment promotion patterns

  • Own RBAC permission model: analyst/engineer roles, service-user provisioning, solution-owner access patterns, least-privilege via Okta and App Cafe

  • Design and evolve dbt Mesh and data mesh boundaries across business domains (Finance, Marketing Ops, CPX, others)

  • Configure and operate Snowflake account infrastructure: warehouses, resource monitors, query tags, replication, account parameters, Iceberg, External Access Integration, compute pools

  • Own integration with Atlan for enterprise data cataloging, lineage, and metadata lakehouse governance

  • Define integration standards for orchestration (Airflow), ingestion (Fivetran), data sharing, and ELT tooling with guardrails for domain teams

AI & Agentic Data Infrastructure

  • Design Snowflake data architecture patterns for AI/agentic workflows: structured/semi-structured data access for LLM pipelines, context retrieval, feature store integrations, Snowflake Cortex or external model frameworks

  • Build and operate MCP (Model Context Protocol) server infrastructure exposing Snowflake data to AI agents/LLM workflows, defining access patterns, routing logic, and guardrails

  • Own analytical agent evaluation framework: tooling, standards, and automated testing for agent accuracy, hallucination risk, and coverage across governed data domains

Security, Governance & Cost

  • Partner with GRC and Security on FedRAMP boundary controls, data sanitization, field-level masking, and security reviews for new schemas/integrations

  • Drive operational discipline via query-tag attribution, warehouse sizing strategy, and showback alignment with business departments

Enablement & Ecosystem

  • Enable multi-model data consumption (BI, business/AI applications, analysts, developers) through Snowflake connectivity, performance tuning, and access patterns within guardrails

  • Define standards for reverse-ETL and operational workloads (Salesforce, OpenAir, Workato, Fivetran, similar); delegate execution to domain teams within guardrails

What You'll Need

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Math, Finance, Statistics, or related discipline (or equivalent practical experience)

  • 8+ years in data or platform engineering, including 3+ years owning Snowflake account/platform operations at enterprise scale

  • Demonstrated architectural judgment balancing standardization, domain autonomy, cost, security, performance, and buy/build/adopt decisions at enterprise scale

Preferred Qualifications

Technical

  • RBAC model design, service-user provisioning, SSO/Okta integration for Snowflake

  • Semantic layer design on Snowflake (semantic views, verified queries, metadata for human/AI consumers)

  • MCP server or equivalent AI data gateway infrastructure for LLM-powered workflows

  • Analytical agent evaluation frameworks: accuracy testing, hallucination detection, coverage validation

  • Data governance: row/column masking, secure views, data cataloging (Atlan), compliance-boundary design (FedRAMP, SOX)

  • Advanced SQL query design and tuning for performance, cost, and accuracy in Snowflake

  • AWS data services (S3 staging, IAM, Secrets Manager) supporting Snowflake workloads

  • Python or scripting for platform automation and provisioning

  • dbt (Core or Cloud) and dbt Mesh or multi-project data mesh patterns

  • BI/analytics tools (QuickSight, Omni, Sigma, Tableau); experience evaluating or migrating BI tooling

  • Orchestration/ingestion tools (Airflow, Fivetran, Workato, or similar)

  • Performance and cost optimization: warehouse tuning, query analysis, resource monitors, query tags

  • Agile/Sprint environment experience

  • SnowPro Core, Advanced, or Architect certification (preferred)

Leadership

  • Excellent verbal/written communication; ability to translate platform strategy for business, technical, and executive audiences

  • Proven ability to influence technical direction and drive alignment across teams without direct authority

  • Strong planning and prioritization to manage strategic roadmap, operational work, and emerging tech evaluations concurrently

  • Comfort navigating ambiguity, defining structure, and driving decisions with incomplete information under organizational complexity

  • Experience leading or contributing to cross-functional initiatives

  • SaaS or subscription-based business experience

  • Track record scaling enterprise data platforms across multiple business domains

Working Conditions

  • Less than 10% travel

  • Reliable internet access for remote working opportunities

Workiva will not provide visa sponsorship for this position. Candidates must be authorized to work in the U.S. on a permanent basis.

How You'll Be Rewarded

Salary range in the US: $129,000.00 - $210,000.00

A discretionary bonus typically paid annually

Restricted Stock Units granted at time of hire

401(k) match and comprehensive employee benefits package

The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors.

Why Join Workiva

Workiva is the platform designed to bring confidence, control, and a competitive edge to the world's most complex organizations. Our AI-powered platform unifies finance, risk, and sustainability on a single, secure foundation-ensuring data is trusted, traceable, and ready to act on. With an unbroken path from source to output, leaders gain confidence in their numbers, visibility into current and emerging risks, and the ability to move with speed and precision in a constantly changing world.

At Workiva, you'll bring technology to market that executives, boards, and regulators depend on. The work you do here helps organizations navigate uncertainty, maintain trust, and make decisions that stand up to scrutiny. If you're energized by meaningful challenges, inspired by collaborative teams, and motivated to help organizations turn uncertainty into advantage, we'd love to meet you.

Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic.

Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email talentacquisition@workiva.com.

Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards.

Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment.

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