Software Engineer

Career Area

Technology, Digital and Data

Job Description

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, youre joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We dont just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Roles And Responsibilities

• - **Proficient in Python (5 years)** - familiar with PEP standards, linters (ruff, pylint), package managers (poetry, uv)
• - 1 year of SQL; General knowledge on databases and storage layers
• - 3 years experience with AWS (Dynamo, RDS, S3, Kinesis, EventBridge, SNS, SQS), Fargate, Lambda);
• - **Experience building and deploying applications on AWS**.
• - Knowledge of AWS infrastructure and services
• - 5 years experience with object oriented programming, test driven development,
• - 5 years experience with **unit, integration and regression testing**;
• - Experience with CI/CD tools such as Github Actions (AzDO pipelines)
• - **Experience writing Python Rest APIs** - FastAPI, Flask, Django
• - **Experience working in a team** - be able to read other peoples code
• - **Level of English sufficient to work in an international team (B1+); Soft Skills (Required) Ability to communicate at a high level. Proactive, self motivated. Able to move projects forward quickly Ability to quickly learn and utilize new technologies**
• - Git at a sufficient level (be able to contribute to a team repo, resolve merge conflicts)
• - Docker
• - Nice to have:
• - Golang
• - Langchain or any other AI/Agentic framework
• - Airflow or any other orchestration tool (Dagster, Luigi, Prefect)
• - Azure Cloud (esp. its AI suite)
• - AI orchestration frameworks like LangChain, LangGraph
• - MLFlow or any other model versioning tool
• - Data science background - familiarity with DS workflows, problems, models, evaluation patterns, etc.
• - Data processing frameworks: PySpark, Dask, Ray, Pandas, Polars, DuckDB (not all of them)
• - Javascript (writing github actions) and frontend frameworks (React, Vue, Svelte)/htmx