Top Tech Jobs & Startup Jobs

Leads advanced data science initiatives for Caterpillar’s Service Events domain. Develops and productionizes machine learning and statistical models using large-scale structured and unstructured data, including NLP and predictive analytics. Directs data acquisition, transformation, modeling, and optimization efforts; defines analytical problems and success criteria with stakeholders; communicates findings through visualization and storytelling; and provides technical leadership, coaching, and mentoring across cross-functional teams.

Owns the common services product area for Cat Foresight, connecting customers, field service, and development teams. Responsibilities include managing customer relationships, evaluating feedback, leading design changes and root cause analysis, conducting UAT and business sign-off testing, analyzing product performance, and aligning short-term enhancements with long-term strategy. The role requires collaboration across engineering, sales, and field support, with preferred fleet management, data integration, web solution, and construction operations experience.

Lead the Power & Energy segment’s data architecture vision, strategy, target-state roadmap, conceptual and enterprise data modeling, governance standards, security, metadata, lineage, and solution design. Partner with data engineering, analytics, IT, business stakeholders, and executives to ensure scalable, reusable, high-quality data ecosystems aligned with business needs. Guide data modernization, cloud migration, and digital transformation initiatives.

Build, enhance, deploy, and operate secure enterprise web applications and reporting solutions. Develop full-stack systems using Python, Django, React, JavaScript, HTML, CSS, and SQL; manage Azure cloud deployments, CI/CD, source control, monitoring, testing, and continuous improvement. Collaborate with Finance, IT, Operations, and business stakeholders to translate needs into scalable solutions, conduct code reviews, assess emerging technologies, and communicate application risks and performance insights.

Leads product strategy, architecture alignment, platform adoption, and infrastructure roadmaps for Caterpillar’s autonomy ecosystem. Defines system-level epics, features, acceptance criteria, shared services, integration standards, and foundational technology investments across multiple scrum teams and technical domains. Coordinates architecture, engineering, data, safety, deployment, and infrastructure stakeholders; manages dependencies, technical debt, risks, tradeoffs, platform adoption, scalability, security, and operational readiness.

Leads Caterpillar’s Advanced Technology Pod within AI R&D, setting the applied AI vision and shaping high-impact initiatives. Oversees production-intent prototypes, reference architectures, evaluation standards, and responsible AI practices. Manages senior data scientists and AI engineers while partnering with product, engineering, business, research, customers, dealers, and technology partners. Translates emerging AI research into scalable, production-ready concepts and communicates technical strategy and business outcomes to executives.

Lead technical design and delivery of scalable backend microservices using Java and Spring Boot. Provide architectural guidance, mentor engineers, establish secure AI-assisted development workflows, drive cloud-native deployments on AWS/Azure, and ensure software quality through reviews, testing, and operational readiness. Influence cross-functional delivery and build reusable platform patterns that enable production AI/agent integrations and platform scalability.

Design and govern data assets, develop pipeline specifications with field-level mapping and quality rules, document domain data models and canonical formats, design scalable databases and ETL solutions, and solve complex data problems to support Cat Digital. Hybrid work: telecommute one day per week.

Design, develop, support, and improve enterprise Adobe Experience Manager platform capabilities. Build integrations and enhancements across AEM Sites, Assets, Cloud Manager, CI/CD pipelines, and related digital experience technologies. Improve platform reliability, security, performance, and maintainability through cloud migration, modernization, automation, monitoring, and observability. Lead incident resolution and root-cause analysis while collaborating with product, engineering, infrastructure, security, and vendor teams in an agile environment.

Develop and optimize generative AI and large language model solutions, including fine-tuning, agentic workflows, retrieval-augmented generation, and experimentation. Research emerging algorithms, evaluate model performance using automated and human-in-the-loop methods, implement safety guardrails, and integrate AI services with cloud platforms. Mentor junior data scientists and guide technical approaches for AI-driven products.