Jobs at Caterpillar

Own product data quality for Prime and Parts digital experiences by profiling data with SQL and Python, building scorecards and dashboards, detecting anomalies, automating exception triage, defining content standards, validating migrations, and communicating data health trends. The role partners with engineering and business stakeholders to improve governance, reconciliation, enrichment, and scalable data quality processes across product domains.

Leads technical strategy, architecture, delivery, quality, and reliability for the PIM platform. Manages Akeneo engineering and the Informatica P360 migration, reviews solution designs and integrations, oversees backlog and release readiness, resolves technical issues, and manages vendor/SOW activities during the transition.

Leads digital insights project delivery from planning through launch and post-launch follow-up. Manages scope, schedules, dependencies, risks, requirements, acceptance criteria, stakeholders, workstreams, implementation, testing, governance, and reporting. Partners with analysts, product owners, customer-facing teams, and business and technical contributors to align project outcomes with business objectives. Uses data, user feedback, and adoption measures to support decisions and evaluate results.

Owns vision, roadmap, backlog, and delivery for software coordinating autonomous construction machines, with emphasis on exception management and remote operation. Partners with design, research, engineering, customers, dealers, and field support to prototype concepts, validate user needs, prioritize features, resolve issues, and drive adoption. The role requires product management, software business knowledge, AI-assisted prototyping, business analysis, communication, decision-making, and software engineering understanding.

Leads software test engineering for Caterpillar’s AI and autonomy programs. Defines AI testing strategy, quality standards, frameworks, tooling, automation, and governance. Manages and develops test engineering leaders and teams, architects model-validation and data-quality solutions, and partners with engineering, product, and data science teams to ensure reliable, safe, compliant systems. Drives continuous improvement through automation, observability, AI-assisted development, and scalable quality practices.

Design, develop, test, integrate, and support software applications within an agile engineering team. Translate requirements into technical solutions, write maintainable Java code, automate workflows, perform application integration and testing, and support ongoing maintenance. The role emphasizes Java, Spring Boot, cloud technologies, microservices, OpenSearch, AWS, and containerized deployments using Fargate and ECS.

Provides production support and platform stability for Azure cloud services and APIs. Owns incident resolution, coordinates cross-team troubleshooting, leads root cause analysis, maintains monitoring and operational runbooks, and drives reliability improvements. The role also supports on-call response, release and rollback processes, knowledge transfer, and operational readiness across distributed cloud services.

Performs data analysis, validation, mining, processing, modeling, and ETL activities on large, diverse datasets. Collaborates with senior team members to build backend data infrastructure, assess data accuracy, identify inconsistencies, and deliver business insights through reporting and visualization. The role uses SQL, Python, machine learning, cloud technologies, data governance, and data quality practices to support digital product development and data-driven decisions.

Provides application security engineering across the software development lifecycle. Responsibilities include managing security defects, consulting with engineers and architects, enabling security testing tools, coordinating penetration testing, measuring application security maturity, and documenting corrective actions. The role requires software development and integration knowledge, cloud experience, and expertise in analyzing and remediating findings from SAST, DAST, SCA, penetration testing, and related security assessments.

Lead the Rental Data Model strategy and dealer integrations, translating rental business needs into scalable data products. Drive data standards, governance, roadmap prioritization, validation, and root-cause analysis while partnering with engineering, analytics, dealers, and stakeholders to ensure data quality and enable trusted reporting and customer experiences.

Leads enterprise marketing technology architecture and multi-year roadmaps across content, digital experience, PIM, commerce, analytics, personalization, identity, and omnichannel platforms. Designs application, data, integration, and infrastructure architectures; guides platform strategy, governance, security, privacy, and lifecycle management. Partners with marketing, product, data, security, and engineering teams, evaluates technologies, leads architecture reviews, resolves complex design issues, directs delivery partners, and mentors technical talent while aligning investments to measurable business outcomes.

Own and evolve dealer-facing product strategy and roadmap for Cat Rentals. Translate dealer and rental business needs into scalable Dynamics 365 and AI-enabled solutions, prioritize backlog, define future workflows, partner with Microsoft/Accenture/engineering, and measure KPIs to improve dealer responsiveness, automation, and customer satisfaction.

Leads the technical vision, architecture, and delivery of enterprise search analytics and ontology solutions for ecommerce. Manages and mentors software engineering teams, integrates platforms, oversees IT service operations and quality, and improves search relevance using NLP, vector search, personalization, machine learning, and performance KPIs. Partners with product, data science, and engineering leaders while driving ontology, metadata, governance, and semantic search adoption across digital commerce.

Leads Caterpillar’s Condition Monitoring Analytics Transformation team and portfolio. Manages 8–12 data scientists while providing hands-on technical guidance on machine learning, AI, predictive maintenance, failure modeling, evidence clustering, persona modeling, and closed-loop learning. Collaborates with commercial, product, engineering, R&D, and MLOps teams to deploy scalable analytics solutions, prioritize resources, drive innovation, and develop team talent.

Own the roadmap, backlog, requirements, prioritization, and delivery of AI-powered customer experiences for Cat.com. Partner with product, UX, engineering, analytics, data science, and business teams to define solutions, conduct experimentation, measure KPIs, and improve customer engagement and discovery. Guide conversational, personalized, recommendation, and decision-support capabilities while ensuring privacy, accessibility, security, scalability, and responsible AI standards. Coordinate stakeholders, manage dependencies, and drive execution across distributed teams.

Leads the technical vision, architecture, development, and operations of Caterpillar’s search platform. Manages and mentors multiple software engineering teams while delivering scalable, high-performance search capabilities for web and mobile applications. Oversees integrations, quality assurance, IT service operations, analytics, and continuous relevance improvements using NLP, vector search, personalization, machine learning, and A/B testing. Partners with product, data science, and engineering leaders to align search initiatives with business objectives.

Develop machine learning, deep learning, statistical, and Generative AI solutions using equipment and telematics data. Build models for anomaly detection, failure prediction, remaining useful life, and risk assessment. Support digital products through reliability monitoring, incident response, automation, connectivity planning, technical analysis, and performance optimization. Partner with engineers and data scientists on AI, analytics, IoT, and digital product initiatives.

Develop and support AI-powered digital solutions across mobile, web, cloud, and enterprise platforms. Responsibilities include designing microservices, enabling APIs, deploying Microsoft Fabric patterns, developing AI agents, building Python data pipelines, testing software, resolving defects, evaluating emerging technologies, and contributing to UI/UX design. The role offers hands-on development, mentorship, and project ownership for candidates with up to two years of experience.

Leads an AI Evaluation Engineering team responsible for validating generative AI products, including intelligent agents and digital assistants. Provides technical direction, manages team performance and development, owns product quality, and establishes engineering best practices. The role requires expertise in GenAI architecture, evaluation methodologies, observability, automated testing, cloud and edge environments, reliability, safety, RAG assessment, and human-in-the-loop validation.

Perform independent software testing and quality assurance for complex applications and infrastructure. Design and execute automated, regression, integration, performance, and user acceptance tests; develop automation frameworks and test code; document and track defects; collaborate with product owners, developers, and end users; and support debugging, continuous integration, delivery, and end-to-end system testing.