Data Scientist, AI Specialist

About the Role

We are seeking a hands-on AI Specialist – Agentic AI & Conversational AI to join Caterpillar’s Business Intelligence and AI team within IT. The role focuses on making enterprise data more accessible, discoverable, and actionable through conversational AI, Large Language Models (LLMs), and agentic workflows.

You will research, prototype, develop, and deploy AI-powered solutions that enable business users to interact with enterprise data using natural language and intelligent automation. You will collaborate with business stakeholders, data engineers, analysts, architects, and technical leadership to transform innovative AI concepts into reliable, scalable, production-ready solutions that deliver measurable business value.

Key Responsibilities

• Design, develop, and deploy conversational AI applications that enable users to access and analyze enterprise data using natural language.
• Build agentic AI workflows and multi-agent systems to automate complex business processes and data-driven tasks.
• Research emerging AI technologies, evaluate frameworks, and rapidly prototype innovative solutions.
• Develop and integrate LLM-powered applications using GPT-based models, enterprise AI services, and modern AI/ML libraries.
• Leverage Azure AI services, Snowflake, Snowflake Cortex, and related technologies to build enterprise-grade AI solutions.
• Implement Retrieval-Augmented Generation (RAG), embeddings, vector search, and semantic search capabilities to improve information retrieval and response accuracy.
• Collaborate with data engineering and analytics teams to integrate AI applications with enterprise data platforms and business intelligence ecosystems.
• Transition AI prototypes into production environments, ensuring scalability, reliability, maintainability, and operational readiness.
• Apply LLMOps practices, including model and prompt versioning, performance monitoring, cost optimization, evaluation, and continuous improvement.
• Establish appropriate safeguards for AI-generated outputs, including validation, access controls, responsible AI practices, and error handling.
• Work closely with business stakeholders to understand requirements, validate prototypes, incorporate feedback, and deliver practical AI-driven business outcomes.
• Communicate technical concepts, implementation approaches, and solution outcomes clearly to technical and non-technical stakeholders.

Requirements & Tech Stack

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• Demonstrated experience delivering AI/ML applications or data-driven solutions in production environments.
• Strong understanding of Large Language Models (LLMs), GPT-based models, conversational AI, and AI agent architectures.
• Hands-on programming experience in Python and modern AI/ML development libraries.
• Strong experience with Azure AI services, Snowflake, and enterprise AI application development.
• Practical experience designing and implementing agentic workflows and multi-agent orchestration.
• Experience integrating AI applications with enterprise data sources, APIs, and backend systems.
• Ability to rapidly prototype, test, evaluate, and iterate on AI-powered solutions.
• Experience deploying and operating AI solutions in enterprise environments.
• Strong analytical, problem-solving, collaboration, and communication skills.
• A strong portfolio of applied AI projects demonstrating practical implementation and business impact.

Technical Skills

• Programming & AI/ML
• Python
• Modern AI/ML libraries and development frameworks
• LLM application development and GPT-based models
• Conversational AI & Agentic Systems
• Conversational AI and natural language interfaces
• AI agents and agentic workflow design
• Multi-agent orchestration
• Tool calling, workflow automation, and API integration
• Cloud & Enterprise AI Platforms
• Microsoft Azure AI services
• Snowflake and Snowflake Cortex
• Enterprise AI application deployment and integration
• Data Retrieval & Knowledge Systems
• Retrieval-Augmented Generation (RAG)
• Embeddings and vector databases
• Semantic search and information retrieval
• Enterprise data integration
• Production Engineering & LLMOps
• AI application deployment and operational support
• Model, prompt, and configuration versioning
• Monitoring, evaluation, and performance optimization
• Cost management, reliability, and scalability
• Responsible AI, access controls, and output validation

Preferred Qualifications

• Proven experience designing and implementing agentic AI workflows for enterprise use cases.
• Hands-on experience with Azure AI, Snowflake Cortex, or comparable enterprise AI platforms.
• Experience building RAG-based applications using embeddings, vector databases, and semantic search.
• Familiarity with LLMOps best practices, including monitoring, evaluation, version control, and cost optimization.
• Experience in financial services or other regulated industries, with an understanding of governance and compliance requirements.
• Experience integrating conversational AI with business intelligence, analytics, and enterprise data ecosystems.
• Demonstrated success transitioning AI prototypes into scalable production applications.

Soft Skills

• Strong communication skills and the ability to explain complex AI concepts to diverse audiences.
• Effective collaboration with business stakeholders, data engineers, analysts, architects, and leadership.
• Innovative mindset with a practical approach to experimentation and problem-solving.
• Adaptability and willingness to incorporate feedback and changing business requirements.
• Strong ownership, accountability, and focus on delivering measurable business outcomes.
• Ability to balance experimentation with production reliability, scalability, and maintainability.
• Commitment to inclusive teamwork and continuous learning.