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Engineering Manager Jobs in Ames, IA (NOW HIRING)

Process Engineer

Nevada, IA · On-site

$80 - $100/hr

The position is based in Winnemucca, NV and reports to the Site Engineering Manager. Responsibilities * Support pre‑commissioning, commissioning, and start‑up activities for the Thacker Pass ...

Software Engineering Manager The Culture Ag Leader was born from a passion and determination to transform agriculture forever. In 1992, Ag Leader changed the industry by bringing real-time yield data ...

Data Engineer

Urbandale, IA · On-site

$80K - $120K/yr

RFA Engineering ( www.rfamec.com ) supports industry-leading clients through the full software ... Manage and optimize storage of diverse data types, including images, raster data, parquet files ...

Senior Project Engineer

Ames, IA · Remote

$101K - $132K/yr

Senior Engineering Manager __ In this role, you will act as a design authority for an engineering discipline with medium complexity. You will complete assignments on multiple projects of moderate ...

Showing results 21-40

Engineering Manager information

See Ames, IA salary details

$45.5K

$143.7K

$170.2K

How much do engineering manager jobs pay per year?

As of Sep 5, 2026, the average yearly pay for engineering manager in Ames, IA is $143,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $169,200.00 per year, depending on experience, location, and employer.

What is an engineering manager?

Engineering Managers are professionals responsible for leading and overseeing engineering teams within an organization. They coordinate projects, manage team members, allocate resources, and ensure that engineering goals align with company objectives. Their role often involves a combination of technical expertise, leadership, and administrative skills to deliver successful engineering solutions on time and within budget.

What are the key skills and qualifications needed to thrive as an engineering manager?

To thrive as an Engineering Manager, you need a strong background in engineering principles, project management, and leadership, typically with a degree in engineering and prior technical experience. Familiarity with project management tools (such as Jira or Asana), version control systems (like Git), and potentially certifications such as PMP or Scrum Master are highly beneficial. Exceptional communication, conflict resolution, and team-building skills distinguish top performers in this role. These abilities are crucial for successfully leading technical teams, delivering projects on time, and aligning engineering output with organizational goals.

How does an engineering manager typically balance technical leadership with people management responsibilities?

Engineering Managers are often required to split their time between technical oversight—such as code reviews, architecture decisions, and project planning—and people management tasks like mentoring, performance reviews, and team development. Striking this balance can be challenging, especially in fast-paced environments. Successful Engineering Managers usually prioritize regular one-on-ones, foster open communication, and delegate technical tasks wisely to ensure both project goals and team morale are maintained. This dual focus helps nurture a high-performing, collaborative team while ensuring technical excellence.

What is the difference between Engineering Manager vs Software Development Manager?

AspectEngineering ManagerSoftware Development Manager
Primary FocusOversees engineering teams, technical projects, and product developmentManages software development teams, project timelines, and coding processes
Required CredentialsBachelor's or master's in engineering, computer science, or related field; technical expertiseBachelor's or master's in computer science, software engineering, or related field; strong coding background
Work EnvironmentEngineering departments, cross-disciplinary teams, technical environmentsSoftware development teams, Agile/Scrum environments, coding-focused settings
Industry UsageCommon in tech, manufacturing, and engineering firmsPrimarily in tech companies, software firms, and IT services

While both roles involve managing technical teams, Engineering Managers typically oversee broader engineering projects and cross-disciplinary teams, whereas Software Development Managers focus specifically on software projects and coding teams. Understanding these distinctions helps in choosing the right career path or job search focus.

Are engineering managers paid well?

Engineering managers typically earn high salaries due to their leadership responsibilities, technical expertise, and experience level. Compensation varies by industry, location, and company size but generally includes base pay, bonuses, and stock options, reflecting the seniority of the role.

What do you do as an engineering manager?

An engineering manager oversees engineering teams, coordinates project planning, and ensures technical goals are met. They manage resources, facilitate communication between teams and stakeholders, and often have technical expertise to guide development processes. Leadership, problem-solving, and knowledge of engineering tools are essential skills in this role.

What are the most commonly searched types of Engineering jobs in Ames, IA?

The most popular types of Engineering jobs in Ames, IA are:

What are popular job titles related to Engineering Manager jobs in Ames, IA?

For Engineering Manager jobs in Ames, IA, the most frequently searched job titles are:

What job categories do people searching Engineering Manager jobs in Ames, IA look for?

The top searched job categories for Engineering Manager jobs in Ames, IA are:

What cities near Ames, IA are hiring for Engineering Manager jobs?

Cities near Ames, IA with the most Engineering Manager job openings:

Infographic showing various Engineering Manager job openings in Ames, IA as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $143,665 per year, or $69.1 per hour.

Sr Machine Learning Engineering Manager - AI Quality and Governance

Workiva, Inc.

Ames, IA • On-site

Other

Retirement

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


Workiva rating

9.9

Company rating: 9.9 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

1st of 247 rated software companies


Job description

Join Workiva as a Sr Machine Learning Engineering Manager - AI Quality and Governance and help establish how we build, evaluate, release, and operate trustworthy AI products at scale. You will lead a multidisciplinary team of software, machine learning, and quality engineers responsible for two connected missions: advancing end-to-end quality across Workiva's AI platform and products, and building shared evaluation and governance capabilities that make our AI systems measurable, observable, reliable, and ready for enterprise use.

Your team's scope spans generative AI and agentic products, including AI platform services, agent frameworks and runtimes, conversational experiences, and RAG/knowledge systems. You will partner across Product, Engineering, Data Science, Security, Risk, and Legal to establish practical quality standards and embed evaluation and governance throughout the AI development lifecycle.

What You'll DoLeadership & Team Development
  • Lead, mentor, and develop a multidisciplinary team of software, ML, and quality engineers

  • Build a culture of technical excellence, quality ownership, experimentation, and continuous improvement

  • Establish clear team priorities while balancing platform investments, product needs, and enterprise risk

  • Recruit engineers with complementary expertise across software quality, ML evaluation, platform engineering, and governance automation

AI Product Quality
  • Define and drive a comprehensive quality strategy for Workiva's AI platform and products, spanning unit, integration, end-to-end, performance, resilience, security, and production testing

  • Establish measurable quality bars, release-readiness criteria, and automated quality gates for AI and agentic capabilities

  • Advance testing approaches for nondeterministic systems, including RAG pipelines, agents, prompts, models, tools, and multi-step workflows

  • Detect regressions, model or data drift, unsafe behavior, and degraded customer experiences before and after release

AI Evaluation Platform
  • Lead architecture and delivery of a scalable, self-service evaluation platform for generative AI, RAG, and agentic systems

  • Enable teams to create, manage, version, and reuse evaluation datasets, golden test sets, task-specific metrics, graders, and benchmarks

  • Support deterministic checks, statistical metrics, model-based graders, human evaluation, adversarial testing, and domain-expert review

  • Build capabilities for offline evaluation, pre-release regression testing, online experimentation, production sampling, and continuous evaluation

  • Ensure evaluation results are reproducible, explainable, actionable, and integrated into developer workflows, CI/CD pipelines, and operational dashboards

AI Governance & Assurance
  • Translate Workiva's Responsible AI principles into practical engineering controls and platform capabilities

  • Build governance into the AI lifecycle through traceability, lineage, versioning, documentation, risk classification, approval workflows, and auditable evidence

  • Partner with Security, Legal, Privacy, Compliance, and Risk teams to define controls that support enterprise and regulated use cases

  • Enable inventories and traceability across models, prompts, datasets, evaluations, tools, knowledge sources, and deployed AI features

Cross-Functional Leadership
  • Collaborate with Product, Program Management, UX, UXR, Data Science, Security, Legal, Risk, and engineering leaders to define quality expectations and roadmaps

  • Influence engineering teams across Workiva to adopt shared evaluation standards, testing practices, observability, and release controls

  • Communicate complex technical tradeoffs, quality signals, and risk findings clearly to technical and non-technical audiences

Operational Excellence
  • Ensure the evaluation and governance platform is secure, scalable, reliable, observable, and cost-effective
  • Define service-level objectives and meaningful operational and quality metrics

  • Champion production readiness, incident response, root-cause analysis, and continuous operational improvement

What You'll NeedMinimum Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)

  • 10+ years in software engineering, ML engineering, quality engineering, or related roles, including 4+ years leading an engineering team

  • Strong software engineering and systems-design fundamentals, with experience delivering and operating production SaaS or platform capabilities

  • Demonstrated experience establishing automated quality practices for distributed, cloud-based products

  • Practical understanding of the generative AI development lifecycle and challenges of evaluating nondeterministic systems

  • Experience with generative AI concepts: LLMs, RAG, embeddings, vector/hybrid search, agents, tool use, and prompt orchestration

  • Experience defining measurable quality criteria using data, experimentation, telemetry, and production signals

  • Experience with cloud-native architectures on AWS, Azure, or GCP.

  • Proven ability to lead senior individual contributors, navigate tehhnical disagreements, and build high-performance cultures

  • Strong communication and cross-functional leadership skills

Preferred Qualifications
  • Master's degree in Computer Science, Engineering, ML, Data Science, or related field.

  • Experience building or operating AI/ML evaluation, experimentation, observability, model-governance, or ML platform capabilities

  • Experience evaluating RAG and agentic systems, including retrieval quality, groundedness, task completion, tool use, and safety

  • Familiarity with evaluation techniques: golden datasets, statistical metrics, model-based graders, human evaluation, red teaming, A/B testing, and drift/regression detection

  • Working knowledge of ML/AI lifecycle practices: dataset management, model/prompt versioning, experiment tracking, deployment, monitoring, and feedback loops

  • Experience translating Responsible AI, model-risk, privacy, security, or regulatory requirements into scalable engineering controls

  • Familiarity with AI risk/governance frameworks (NIST AI RMF, ISO/IEC 42001, or comparable)

  • Experience with Kubernetes, microservices, CI/CD, infrastructure as code, and modern DevOps/MLOps practices

  • Experience supporting enterprise software in regulated or high-assurance environments

Working Conditions
  • Willingness to travel up to 15% for team and corporate meetings

  • Reliable internet access for remote work

How You'll Be Rewarded

Salary range in the US: $193,000.00 - $308,000.00

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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