AI Engineer

Saturn Petcare Inc•Terre Haute, IN

About The Position

The AI Engineer makes Saturn’s data decision-ready by building a reliable data foundation across SAP S/4HANA, Ignition, Excel, and external market data; automating reporting; and applying AI to deliver analysis and recommendations directly to management. The role reports to the CFO and works with the Executive and Plant Leadership Teams. It is hands-on: the incumbent personally builds data models, reports, and AI solutions and is accountable for their accuracy. The role also improves organizational readiness for AI through better source data quality, employee capability building, and responsible data and AI practices. The position establishes and operates a single source of truth, standardizes KPI and master-data definitions, and partners with functions to address the causes of poor data. It automates recurring executive and plant reporting, develops concise decision-oriented outputs, and uses AI to produce commentary and summaries subject to human review. It also applies forecasting, scenario analysis, statistical methods, and AI to identify trends, anomalies, and predictive maintenance opportunities, and quantifies operational impacts on the P&L. The AI Engineer identifies and implements AI and automation use cases with business cases and measured benefits, builds and maintains AI agents and automated workflows connected to company systems, and monitors output quality while retaining human accountability. The role trains and coaches employees, leads adoption of new ways of working, structures company knowledge and process documentation, and maintains responsible-use rules aligned with heristo group policy and recognized frameworks. It supports SAP S/4HANA and business-process optimization, partnering with KAM serv.it, PMO IT saturn petcare, functional teams, and external providers as a business-to-IT translator, including support for process mapping and process mining.

Requirements

Bachelor’s degree in Data Science, Business Analytics, Information Systems, Computer Science, Engineering, Business Administration, or a related field; equivalent demonstrated capability may be considered.
At least 5 years of hands-on experience in data analytics, business intelligence, or data engineering, including personally building and operating reporting solutions.
Demonstrated experience automating recurring reporting and replacing manual spreadsheet processes.
Practical experience delivering AI or automation solutions into productive use, not pilots alone.
Proven ability to translate business and operational needs into working solutions with measurable business impact.
Strong communication, training, and change-management skills, including ability to present to executives; candidates should be prepared to present examples of their own work.
Working-level SQL skills, including independent querying, data modeling, and transformation.
Advanced Excel skills and advanced proficiency in a modern business intelligence platform, including data modeling.
Practical experience extracting and modeling data from an ERP system.
Hands-on application of generative AI in a business setting, including AI agents, workflow automation, retrieval over company documents, and judgment about appropriate uses of AI.
Ability to read and interpret safety rules, operating and maintenance instructions, procedural manuals, and other documents; write routine reports and correspondence; and speak effectively before groups of customers or employees.
Ability to work with probability and statistical inference and apply fractions, percentages, ratios, and proportions to practical situations.
Ability to solve practical problems involving limited standardization and interpret written, oral, diagram, or schedule instructions.
Ability to meet the stated physical demands, with reasonable accommodations where applicable.

Nice To Haves

Master’s degree preferred.
Manufacturing experience strongly preferred.
Power BI preferred; SAP Analytics Cloud is an advantage.
Practical experience extracting and modeling ERP data from SAP S/4HANA is preferred.
Python or an equivalent language for data processing and automation.
Experience with industrial and machine data, including Ignition, historians, MES, OPC-UA, or MQTT.
Experience with a modern data platform such as Microsoft Fabric, Databricks, Snowflake, SAP Datasphere, or SAP Business Data Cloud.
Experience with statistical forecasting or machine learning.
Experience with process-mining tools such as Signavio or Celonis.
Familiarity with AI governance frameworks.
German speaking skills.

Responsibilities

Establish data-entry rules, master-data discipline, and data-quality measurement with business functions, while keeping those functions accountable for the accuracy of the data they create.
Build and operate a single data foundation connecting SAP S/4HANA, Ignition and production systems, Excel-based sources, and external market data such as Nielsen.
Establish consistent KPI and master-data definitions and document calculation logic so reports and AI outputs use consistent figures.
Work with functions to eliminate causes of poor data rather than correcting data downstream.
Automate recurring executive and plant reporting, eliminating manual collection, reconciliation, and formatting.
Inventory existing reports, consolidate duplicates, and retire manual spreadsheets replaced by automated reporting.
Deliver clear executive-level views of performance, its drivers, and recommended actions.
Use AI to generate commentary, variance explanations, and meeting-ready summaries from underlying data, with human review before release.
Develop forecasting, scenario and sensitivity analysis, and early-warning indicators.
Apply AI and statistical methods to financial, operational, machine, quality, and market data to identify trends, anomalies, and predictive maintenance opportunities.
Quantify the financial and P&L impact of operational trends.
Identify, prioritize, and implement AI and automation use cases across functions, each with a business case and measured benefit.
Build and maintain AI agents and automated workflows connected to Saturn’s systems that perform work beyond standalone chat usage.
Test and monitor AI output quality and maintain human accountability for every decision.
Train and coach employees at all levels in practical use of AI, reporting, and automation tools.
Identify where AI changes work and lead adoption of new ways of working while retiring replaced routines.
Make company knowledge and process documentation structured, current, and retrievable for employees and AI systems.
Set and maintain responsible data and AI practices aligned with heristo group policy, the NIST AI Risk Management Framework, ISO/IEC 42001, and the EU AI Act, including protection of customer- and partner-confidential data from external AI services.
Support optimization of SAP S/4HANA and related business processes, ensuring data, reporting, AI, and automation requirements are incorporated into the system landscape.
Partner with KAM serv.it, PMO IT saturn petcare, functional teams, and external providers as a business-to-IT translator; support process mapping and process mining.