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Caterpillar

Makes heavy machinery, engines and gas turbines

Manager; AI Evaluation Engineering

Engineering LeadershipUpdated on Nov 9
Full-timeIn-person

About the Job

Requirements

  • Knowledge of major products and services and product and service groups, with the ability to apply that knowledge appropriately to diverse situations.
  • Knowledge of software development tools and activities, with the ability to produce software products or systems in line with product requirements.
  • Knowledge of the software development life cycle and the ability to use a structured methodology to deliver and manage new or enhanced software products.
  • Knowledge of software quality assurance and testing, including the ability to apply appropriate processes, tools, and techniques to assure quality in software products and systems.

Responsibilities

  • Provide technical support and direction so the team is aligned with company goals and can evaluate advanced AI projects.
  • Oversee the performance of individual team members and the team, identifying and addressing training and development needs.
  • Own the quality of AI engineering products and ensure solutions are robust, reliable, and meet high standards.
  • Establish and supervise implementation of engineering best practices to maintain consistency and excellence in development processes.

Desired Qualifications

  • Lead software quality, test automation, validation, and AI evaluation teams, scaling processes, tools, metrics, and engineering practices across products and enterprise initiatives.
  • Deliver enterprise-scale software and generative AI solutions across hybrid cloud and embedded/edge environments, using CI/CD, automated testing, incident management, feature flags, and progressive deployment strategies such as blue/green and canary deployments.
  • Apply generative AI architecture and system design, including LLMs, SLMs, multimodal, speech, and real-time models; prompt engineering; agentic systems; tool use and orchestration; RAG architectures; vector databases, embeddings, and chunking strategies; LoRA fine-tuning; and MCP and A2A standards.
  • Use AI development and evaluation ecosystems such as Azure, AWS, GCP, Azure AI Foundry, SageMaker, Bedrock, Snowflake Cortex, LangChain, LangGraph, Langfuse, Arize, LangSmith, Humanloop, Ragas, DeepEval, and Phoenix, or similar technologies.
  • Apply AI evaluation methodologies for non-deterministic systems, including metric design, RAG quality assessment, output reliability, safety evaluation, A/B testing, human-in-the-loop validation, and balancing deterministic and probabilistic testing approaches.
  • Apply AI observability and monitoring practices, including tracing, telemetry, evaluation data collection, root-cause analysis, automated test generation, synthetic data creation, scenario expansion, and LLM-assisted evaluation.

About the Company

Caterpillar

Makes heavy machinery, engines and gas turbines

Caterpillar makes construction and mining machines, diesel and natural gas engines, industrial gas turbines and locomotives for contractors, mines, energy companies and data center builders. It is the world's largest maker of construction and mining equipment, and its yellow Cat bulldozers and excavators work in nearly every country. Customers buy or rent machines through independent Cat dealers, while its engines and turbines generate electricity and push natural gas through pipelines. Caterpillar earns money from equipment sales and from the parts and repairs that dealers supply over a machine's working life. It was formed in 1925 when California's Holt and Best tractor companies merged, and it is based in Irving, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Irving, TX
Founded
1925

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