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What You'll Do:
We're looking for a Senior AI Governance Analyst to join our Ethical and Responsible AI (ERAI Governance) Program within Enterprise Data & Analytics. In this high-impact role, you'll help shape how we safeguard the organization while enabling responsible AI innovation. You'll lead the operationalization, management, and continued maturation of the AI risk assessment process, helping ensure AI use across the organization is appropriately assessed, inventoried, monitored, and governed. Working closely with teams across Risk, Governance, Enterprise AI Enablement, Data & Analytics, and Technology, you'll translate regulatory requirements into practical, scalable processes that support innovation and effective risk management. This will include managing a consistent set of policies, standards, and principles to enable the strategic, ethical, and responsible development, deployment, and use of artificial intelligence, data, and analytics while articulating the value of AI governance.You'll have the opportunity to:
- AI Risk Assessment Process: Co-lead the design of the AI use case risk assessment process. Operationalize and continuously mature assessment methodologies, scoring criteria, workflows, controls, guardrails, monitoring requirements, and training to ensure quality, consistency, and adherence to service level agreements (SLAs).
- Operating Model Design & Maturity: Drive the effectiveness and continuous improvement of the AI risk assessment program by overseeing the quality, consistency, completeness, efficiency, and transparency of assessment activities. Monitor assessment queues and turnaround times, remediate at-risk or overdue assessments, identify opportunities to streamline processes, and ensure assessments are conducted in a scalable and reliable manner.
- Cross-Departmental Collaboration: Partner with IT, Risk, Privacy, Compliance, AI Enablement, Technology, Data Science, Data Governance, and business teams to research and resolve AI risk concerns, support AI innovation, and ensure emerging capabilities are implemented ethically, safely, responsibly, and with appropriate governance and oversight.
- Monitoring and Reporting: Develop and deliver dashboards, reporting, and insights related to risk exposure, mitigation effectiveness, regulatory compliance, program performance, operational effectiveness, and governance outcomes. Identify opportunities for improvement across business units and present findings to senior leaders and business partners.
- Stakeholder Engagement: Serve as a trusted advisor to business and technical teams on AI risks, governance requirements, and the AI risk assessment process. Host office hours, deliver training, provide guidance on requirements, and promote the adoption of governance practices.
- Mentorship and Team Development: Mentor and coach junior analysts by sharing governance expertise, best practices, and risk assessment techniques. Foster a collaborative culture focused on continuous improvement, critical thinking, respectful challenge, and leveraging diverse perspectives to achieve the best outcomes.
- Training and Enablement: Develop and maintain training materials, playbooks, and guidance for enterprise-wide adoption of the AI risk assessment process. Demonstrate curiosity and a growth mindset by exploring AI technologies, understanding their opportunities and risks, and identifying responsible ways to improve team outcomes.
- Policy and Compliance Management: Manage the Principal AI Policy and Standards and measure governance compliance and maturity across the enterprise.
- Security: Follow all security policies and procedures to ensure the highest level of system and data confidentiality, integrity, and availability.
Who You Are:
- Bachelor's degree or equivalent work experience.
- 8+ years of professional experience in risk management, data governance, privacy, compliance, legal, or related disciplines, with 3+ years focused on AI governance, responsible AI, AI risk management, or related AI oversight activities.
- Demonstrated experience leading transformational change initiatives, including designing and implementing new frameworks, processes, operating models, or organizational capabilities while driving stakeholder adoption and measurable business outcomes.
- Skilled at collaborating with diverse stakeholders and influencing outcomes without formal authority.
- Strong mentorship skills and the ability to lead and guide others without direct leadership responsibilities.
- Excellent communication skills with the ability to present to audiences ranging from executive leadership to individual contributors and translate complex topics into clear, actionable insights.
Skills That Will Help You Stand Out
- Previous AI Governance experience
- Experience with Credo.AI and/or ServiceNow
- Experience designing, building, or implementing AI solutions
- Previous experience in a highly regulated industry
- Experience with Data Governance and/or Analytics Governance tools
Salary Range Information: Salary ranges below reflect targeted base salaries. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation for all roles will be based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer. Salary Range: $135000 - $152000 / year Time Off Program: Flexible Time Off (FTO) is provided to salaried (exempt) employees and provides the opportunity to take time away from the office with pay for vacation, personal or short-term illness. Employees don’t accrue a bank of time off under FTO and there is no set number of days provided. Pension Eligible: Yes Additional Information: Work Environment
This role offers in-office, hybrid (blending at least three office days in a typical workweek), and remote work arrangements (only if residing more than 30 miles from Des Moines, IA, Raleigh, NC, or Charlotte, NC). You’ll work with your leader to figure out which option may align best based on several factors. Work Authorization/Sponsorship
At this time, we're not considering candidates that need any type of immigration sponsorship now or in the future or those needing work authorization for this role. (This includes, but is not limited to students on F1-OPT, F1-CPT, J-1, etc.)
Nonimmigrant Workers and Green Card for Employment-Based Immigrants
Investment Code of Ethics
For Principal Global Investors positions, you’ll need to follow an Investment Code of Ethics related to personal and business conduct as well as personal trading activities for you and members of your household. These same requirements may also apply to other positions across the organization.
Experience Principal
At Principal, we value connecting on both a personal and professional level. Together, we’re imagining a more purpose-led future for financial services – and that starts with you. Our success depends on the unique experiences, backgrounds, and talents of our employees. And we support our employees the same way we support our customers: with comprehensive, competitive benefit offerings crafted to protect their physical, financial, and social well-being. Check out our careers site to learn more about our purpose, values and benefits. Principal is an Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Posting Window: We will accept applications for 3 full days following the Original Posting Date, after which the posting may remain open or be removed based upon applications received. If we choose to post the job again, we will accept additional applications for at least 1 full day following the Most Recently Posted Date. Please submit applications in a timely manner as there is no guarantee the posting will be available beyond the applicable deadline. Date First Posted (TTF): 10/2/2026 Latest Post Date: Careers - US: 10/2/2026 LinkedIn Remote Hashtag
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Salary Context
This $135K-$152K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Principal Financial Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,866 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($143K) sits 32% below the category median. Disclosed range: $135K to $152K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Principal Financial Group AI Hiring
Principal Financial Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Des Moines, IA, US. Compensation range: $152K - $152K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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