Develop detailed architecture deliverables to solve business problems through agentic AI systems and patterns.
Ultimately, delivering full-stack prototypes and production solutions.
You will act as a technical expert collaborating with a team of dedicated data scientists, IT professionals, software engineers, accountants, and ERP knowledge owners to deliver AI and Advanced Analytics solutions in support of Caterpillar’s enterprise-scale accounting data system.
Design AI application's technical infrastructure, including orchestration layers, tool integrations, data retrieval patterns, and testing approaches.
Evaluate and deploy of emerging AI technologies and frameworks to enhance Global Finance agentic capabilities.
Translate business requirements into AI solution designs and collaborating with cross-functional teams to deliver results.

Requirements

Deep experience designing and building agentic AI systems, including multi-agent architectures, tool use and orchestration patterns
Experience designing and implementing production AI agent systems using frameworks like LangChain, LangGraph, Semantic Kernel, or similar orchestration tools
Strong understanding of LLM capabilities, limitations and deployment patterns (prompt engineering, RAG, function calling, context engineering)
Experience evaluating and integrating AI/ML infrastructure components (vector databases, embedding models, orchestration layers, observability tools)
Broad software engineering background including API design, authentication/authorization patterns, and enterprise integration
Ability to translate complex technical concepts for non-technical stakeholders and influence architecture decisions across teams.
Track record of staying current with rapidly evolving AI landscape and bringing practical recommendations to the table
Experience with MLOps/LLMOps practices, model monitoring, or production AI systems at scale
Proven track record of solving complex entity resolution challenges at scale
Hands-on experience with Neo4J, AWS Neptune, or CosmosDB, specifically applied to ER or MDM
Deep expertise in Snowflake architecture and optimization.
Experience utilizing OLAP databases (e.g., DuckDB) and in-memory/column stores (e.g., Redis) for performance optimization.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

agentic AI systemsmulti-agent architecturesLangChainLangGraphSemantic KernelLLM capabilitiesMLOpsmodel monitoringSnowflake architectureOLAP databases

Soft Skills

collaborationtechnical communicationinfluenceproblem-solvingadaptability