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About This Role
Internal Audit Assistant Director \- Data Analytics \& Artificial Intelligence \- Chicago, IL Decatur, IL or Erlanger, KY
ADM's Internal Audit function is undergoing a strategic transformation — embedding advanced analytics and artificial intelligence at the core of how we deliver assurance, manage risk, and add value across the enterprise. To lead this transformation, we are seeking an Asst. Director, Data Analytics \& Artificial Intelligence based in Chicago, IL.
Reporting to the Chief Audit Executive, this Director will serve as the primary architect of ADM Internal Audit's AI and analytics strategy — responsible for agentizing the audit process, deploying intelligent automation, designing next\-generation workflows, and building a data\-fluent audit organization from the ground up. This is a high\-visibility, high\-impact role that sits at the intersection of audit, technology, and organizational transformation.
KEY RESPONSIBILITIES
AI Strategy \& Audit Agentization* Define and own the multi\-year AI and analytics roadmap for Internal Audit, aligning it with ADM's broader enterprise data strategy.
- Lead the end\-to\-end deployment of AI agents across the audit lifecycle — risk assessment, scoping, fieldwork, testing, reporting, and issue follow\-up.
- Identify and prioritize high\-value opportunities to automate manual, repetitive audit procedures through intelligent agents and robotic process automation (RPA).
- Partner with ADM's enterprise AI, data engineering, and IT teams to access data assets and integrate audit tooling into the broader technology stack.
- Evaluate and implement best\-in\-class audit technology platforms, AI co\-pilot tools, and large language model (LLM) applications relevant to internal audit.
Process Design \& Innovation* Re\-engineer core audit processes to operate in an AI\-augmented environment — redesigning workflows, control testing approaches, and documentation standards.
- Establish a continuous auditing and continuous monitoring (CA/CM) capability, enabling real\-time risk signals and always\-on audit coverage across critical processes.
- Develop and maintain a suite of reusable analytics tools, data models, and automated testing scripts that audit teams can deploy across engagements.
- Drive standardization of data ingestion, transformation, and analysis pipelines to ensure consistency, auditability, and scalability.
Talent Development \& Upskilling* Design and lead a structured analytics and AI upskilling program for the full Internal Audit team — spanning foundational data literacy through advanced AI fluency.
- Create a tiered competency framework aligned to roles (Staff Auditor through Assistant Director), with targeted learning paths, hands\-on labs, and applied project experience.
- Embed analytics specialists alongside traditional audit teams on engagements, creating a "BIE\-style" model where data capabilities are integrated into every project.
- Champion a culture of curiosity, experimentation, and continuous learning; recognize and reward innovation by team members.
- Serve as the internal center of excellence for analytics and AI — coaching teams, fielding questions, and building institutional knowledge.
Assurance \& Risk Coverage* Lead and oversee data\-driven audit engagements, applying advanced analytics to evaluate controls, detect anomalies, and surface insights not visible through traditional sampling.
- Incorporate AI\-generated risk signals into the annual audit plan and dynamic risk assessment process; provide the CAE with data\-backed perspective on emerging risks.
- Ensure appropriate governance, bias controls, and explainability standards are applied when AI outputs inform audit conclusions.
- Prepare and present executive\-ready deliverables — translating complex analytical findings into clear narratives for the Audit Committee, CFO, and senior management.
Stakeholder Partnership* Build trusted relationships with ADM's CFO, Controller, Chief Data Officer, and CIO organizations to align on data access, AI initiatives, and joint priorities.
- Represent Internal Audit in enterprise\-wide AI governance forums; contribute to responsible AI policy and ethical use standards.
- Coordinate with external auditors on data analytics methodologies to ensure alignment and avoid duplication of effort.
REQUIREMENTS
Education \& Certification* Bachelor's degree in Accounting, Finance, Data Science, Computer Science, or a related field; advanced degree preferred.
- CPA, CIA, or CISA strongly preferred; data\-related certifications (e.g., AWS, Azure, Google Cloud, Databricks) a plus.
Experience* 12\+ years of progressive experience across internal audit, external audit (Big 4\), or data/analytics roles within a large, complex organization.
- Demonstrated track record designing and deploying AI or advanced analytics solutions in an audit, risk, finance, or compliance context.
- Experience leading or significantly contributing to digital transformation or process automation initiatives.
- Prior people leadership experience with a passion for coaching, developing, and retaining talent.
- Experience in product ownership or familiarity/certification in agile methods and frameworks
Technical Skills* Proficiency in analytics and data platforms: Python, SQL, Power BI, Tableau, Alteryx, or equivalent.
- Working knowledge of AI/ML frameworks and generative AI concepts (LLMs, prompt engineering, agentic architectures, RAG).
- Familiarity with cloud data environments (Azure, AWS, Snowflake, Databricks) and data governance principles.
- Experience with ERP systems and audit management platforms.
- Strong command of Microsoft 365 productivity suite including Power Automate, Copilot, and Excel.
Leadership \& Communication* Exceptional executive presence — able to communicate complex analytical and technical content to non\-technical audiences including the Audit Committee and C\-suite.
- Strategic thinker who can translate ambiguous organizational goals into executable roadmaps and measurable outcomes.
- Collaborative influencer skilled at building consensus across functions, geographies, and seniority levels.
- High degree of intellectual curiosity and comfort operating in rapidly evolving, ambiguous environments.
Excited about this role but don’t think you meet every requirement listed? We encourage you to apply anyway. You may be just the right candidate for this role or another one of our openings.
ADM requires the successful completion of a background check.
REF:111611BR
Base pay offered may vary depending on multiple individualized factors, including market location, job\-related knowledge, skills, and experience. Hourly and salaried non\-exempt employees will also be paid overtime pay when working qualifying overtime hours.
If hired, employees will be in an “at\-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
The pay range for this position is expected to be between:
$151,000\.00 \- $283,000\.00
Salaried Incentive Plan
The total compensation package for this position will also include annual bonus and a long\-term incentive plan
Benefits and Perks
Enriching the quality of life for the world begins by taking care of our colleagues. In addition to competitive pay, we support your diverse needs with a comprehensive total rewards package to enhance your well\-being, including:
- Physical wellness – medical/Rx, dental, vision and on\-site wellness center access or gym reimbursement (as applicable).
- Financial wellness – flexible spending accounts, health savings account, 401(k) with matching contributions and cash balance plan, discounted employee stock purchasing program, life insurance, disability, workers’ compensation, legal assistance, identity theft protection.
- Mental and social wellness – Employee Assistance Program (EAP), Employee Resource Groups (ERGs) and Colleague Giving Programs (ADM Cares).
Additional benefits include:
- Paid time off including paid holidays.
- Adoption assistance and paid maternity and parental leave.
- Tuition assistance.
- Company\-sponsored training and development resources, such as LinkedIn Learning, language training and mentoring programs.
- Benefits may vary for bargained locations, confirm benefit eligibility with your recruiter.
\#IncludingYou
Diversity, equity, inclusion and belonging are cornerstones of ADM’s efforts to continue innovating, driving growth, and delivering outstanding performance. We are committed to attracting and retaining a diverse workforce and create welcoming, truly inclusive work environments — environments that enable every ADM colleague to feel comfortable on the job, make meaningful contributions to our success, and grow their career. We respect and value the unique backgrounds and experiences that each person can bring to ADM because we know that diversity of perspectives makes us better, together.
We welcome everyone to apply. We are committed to ensuring all qualified applicants receive consideration for employment regardless of race, color, ethnicity, disability, religion, national origin, language, gender, gender identity, gender expression, marital status, sexual orientation, age, protected veteran status, or any other characteristic protected by law
About ADM
At ADM, we unlock the power of nature to provide access to nutrition worldwide. With industry\-advancing innovations, a complete portfolio of ingredients and solutions to meet any taste, and a commitment to sustainability, we give customers an edge in solving the nutritional challenges of today and tomorrow. We’re a global leader in human and animal nutrition and the world’s premier agricultural origination and processing company. Our breadth, depth, insights, facilities and logistical expertise give us unparalleled capabilities to meet needs for food, beverages, health and wellness, and more. From the seed of the idea to the outcome of the solution, we enrich the quality of life the world over. Learn more at www.adm.com.
Req/Job ID
111611BR
\#LI\-Onsite
Ref ID
\#LI\-NA1
Salary Context
This $151K-$283K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At ADM, 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 $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. Disclosed range: $151K to $283K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
ADM AI Hiring
ADM has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Decatur, IL, US. Compensation range: $283K - $283K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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