Interested in this AI/ML Engineer role at Commerce Bank?
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About This Role
About Working at Commerce
Building a career here is more than just steps on a ladder. It’s about helping people find financial safety and success, helping businesses thrive, and making sure people and their money are taken care of. And our commitment doesn’t stop there. Our culture is about our people, the ones in our communities and the ones that work with us.
Here, you’ll find opportunities to grow and learn, to connect with others, and build relationships with the people around you. You’ll have the space and resources to grow into the best version of yourself. Because our number one investment is you.
Creating an award\-winning culture doesn't come easy. And after 160 years, we know Commerce Bank is only at its best when our people are. If this sounds interesting to you, keep reading and let’s talk.
Compensation Range
Annual Salary: $119,000\.00 \- $163,000\.00 (Amount based on relevant experience, skills, and competencies.)
At Commerce Bank, innovation and creativity are the driving forces behind our IT team's success. We are catalysts of transformation who power applications, secure networks, and implement cutting\-edge initiatives that propel our business units forward. The banking industry's rapid evolution provides us with an exciting opportunity to continuously learn, grow, and harness new technologies that elevate the experience for our customers. What sets Commerce Bank apart is our company culture and leadership, areas in which we continually invest. This commitment fosters innovation, enhances customer and employee experiences, while reinforcing our belief that our diverse team is our greatest competitive advantage. We actively seek candidates who share our passion for technology and bring fresh perspectives to the table. A diversity of backgrounds, experiences, and viewpoints allows us to develop truly innovative solutions that meet the evolving needs of our banking community. Join us in shaping the future of banking technology. At Commerce Bank IT, you'll find a culture of equity, belonging, and endless opportunities to make a lasting impact. Help us drive innovation that raises the bar for our industry.
About This Job
The main purpose of this job is to be the owner of the AI Enablement product/product line and the associated AI services, and partner with business product owners, the Enterprise Data \& Analytics Office (EDAO), the AI Governance Working Group, and the AI Domain Architect to integrate and organize business and technical aspirations into executable strategy. The AI Service Owner provides the single point of accountability for AI enablement services across IT — including the Microsoft Copilot family, generative and agentic AI platforms, model lifecycle, and the intake, prioritization, and operating model that supports responsible, consistent AI adoption across the bank.
Essential Functions
- Accountable for the technical strategy and architecture designs that realize the joint business and IT feature set for AI enablement services, including Microsoft 365 Copilot, Azure OpenAI/AI Foundry, Copilot Studio, Power Platform AI, and other generative and agentic AI capabilities
- Orchestrate technology change lifecycles in the AI product line that sustain the technical viability of the products and advance the core features in accordance with strategy, including model versioning, platform upgrades, and responsible AI controls
- Monitor the service quality outcomes for AI services, report on service activity to business stakeholders and the AI Governance Working Group, and orchestrate improvements as necessary to meet the negotiated service levels
- Conduct market research in collaboration with bank product owners and the AI Governance Working Group to inform AI technology strategy and prevent ad\-hoc, one\-off implementations
- Lead IT efforts in partnership with the business to evaluate new AI technologies, models, and providers that support enablement, including responsible AI, security, and compliance assessments
- Analyze and define efficient, cost\-effective AI solutions to support company objectives, business processes, and functional requirements through detailed knowledge of complex issues including model risk, data sensitivity, and emerging regulatory expectations
- Partner with internal stakeholders, business product owners, EDAO, Information Security, Risk, Legal, and Compliance to integrate business and technical needs into a comprehensive AI strategy and execution roadmap
- Develop the technical strategy and design for one or more AI products / services, including platform readiness, AI use case intake, and prioritization frameworks
- Negotiate, monitor, and report operational service levels for one or more AI products or services, including availability, cost\-to\-serve, model performance, and responsible AI metrics
- Sponsor AI product / service / product line technical improvement initiatives as required to meet and sustain negotiated service levels
- Provide oversight and regular reporting of AI product and service change initiatives to executive leadership and the AI Governance Working Group, including business case development and sizing
- Conduct and participate in the analysis of business processes and functional requirements where AI is being introduced or expanded
- Manage the daily rhythm of discussions that clarify and resolve requirements during AI solution design, development, evaluation, testing, and release
- Create an annual budget for operating and capital expenses required to sustain or improve the AI product / service / product line
- Potential to include management of direct reports (e.g., AI Domain Architect, AI Engineer, AI Enablement Specialist) to assist in carrying out AI service planning and domain architecture related activities
- Perform other duties as assigned
Work Schedule
- Hybrid Schedule: Minimum 2 days in office per week
Knowledge, Skills \& Abilities Required
- Working knowledge of the AI/ML and generative AI technology landscape — including Microsoft 365 Copilot, Azure OpenAI/AI Foundry, Copilot Studio, agentic AI, RAG patterns, and prompt engineering — to use when collaborating with business stakeholders to integrate and organize business and technical aspirations into executable strategy
- Working knowledge of responsible AI principles, model risk management, AI governance frameworks (e.g., NIST AI RMF), and emerging AI regulatory expectations applicable to financial services
- Strong knowledge of agile SDLC, communication and change leadership principles and practices, and vendor management and contract negotiation tactics, including AI vendor and model provider agreements
- Solid knowledge of product management best practices, functional design, and application delivery methodology applied to AI products and services
- Working knowledge of design thinking, APIs and integration concepts, big data, and UI/UX design as they apply to AI\-enabled workflows and Copilot experiences
- Experience with budgeting for operating expenses and capital investments, including AI consumption\-based cost models
- Strong business relationship management skills, with the ability to act as a single point of accountability for AI enablement across IT and the lines of business
- Strong strategic development and technical design skills for AI platforms and reusable patterns
- Service planning skills, including AI use case intake, prioritization, and lifecycle management
- Deep working knowledge of IT products, services, policies, processes, and organization
- Advanced problem\-solving skills for complex situations, including ambiguity inherent in emerging AI capabilities
- Motivated and organized self\-starter with strong attention to detail and the ability to manage multiple priorities
- Inquisitive, agile, and strong team player with excellent written, verbal, and interpersonal communication skills
- Strong business acumen with ability to document and clearly articulate complex concepts to various levels of technical and non\-technical stakeholders
- Ability to remain adaptable and resilient to all situations with an optimistic outlook and cast a positive shadow that is aligned with our culture and Core Values
- Outstanding interpersonal and relationship building skills with the ability to effectively communicate with all levels of the company, clearly expressing ideas and concepts both verbally and in writing
- Strong leadership competencies with ability to motivate team members and foster a positive team environment that gives way to collaboration and unified goals
- Advance level proficiency with Microsoft Word, Excel, Teams and Outlook
Education \& Experience
- Bachelor’s degree in information technology or related field, or equivalent combination on education and experience required
- 6\+ years IT experience required
- 4\+ years technical product or project management experience required
- 3\+ years leadership/supervisory experience preferred
- *Must be eligible to work in the US without sponsorship now or in the future.*
\*\*Level of role is determined by knowledge, experience, skills, abilities, and education.
\*\*\*For individuals applying, assigned and/or hired to work in areas with pay transparency requirements, Commerce is required by law to include a reasonable estimate of the compensation range for some roles. This compensation range is for the IT Service Owner \& Senior Owner job and contemplates a wide range of factors that are considered in determining most appropriate job level and making compensation decisions, including but not limited to location, skill sets, education, relevant experience and training, licensure and certifications, and other business and organizational needs. The disclosed range estimate has not been adjusted for any applicable differentials (geographic, bilingual, or shift) that could be associated with the position or where it is filled. At Commerce, compensation decisions are dependent on the facts and circumstances of each situation. A reasonable estimate of the current base pay is $119,000 to $163,000 annually. This position will be eligible for additional compensation through performance\-based incentive plan(s) that will correspond to meeting performance goals.
\#LI\-CW1
\#LI\-Hybrid
The candidate selected for this position may be eligible for the following employment benefits: employer sponsored health, dental, and vision insurance, 401(k), life insurance, paid vacation, and paid personal time. In addition, we offer career development, education assistance, and voluntary supplemental benefits.
Location: 922 Walnut St, Kansas City, Missouri 64106
Time Type:
Full time
Salary Context
This $119K-$163K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Commerce Bank, 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 Required
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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($141K) sits 36% below the category median. Disclosed range: $119K to $163K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Commerce Bank AI Hiring
Commerce Bank has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Kansas City, MO, US. Compensation range: $163K - $163K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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