Engineer I, Artificial Intelligence

The Role:

The mission of this role is todesign develop deploy and operationalize agentic AI systems and scientific machine learning solutionsthat automate complex multi-step technical workflows.

The AI Engineer will focus on buildingLLM-driven goal-oriented AI agentsanddata-driven models for physical systems integrating them with data tools sensors and simulation workflows.

This is a hands-on implementation-focused role suited for someone passionate aboutagentic AI scientific ML and real-world engineering problem solving. Exposure to Modeling & Simulation (CFD/FEA) is beneficial but not mandatory.

In this role you will:

• Design and developagentic AI systemsfor multi-step reasoning tool usage and workflow orchestration

• BuildLLM-driven workflows and Python-based pipelinesintegrating agents with data APIs and engineering tools

• Develop and applyscientific machine learning modelsusing experimental sensor and simulation data

• Createdata pipelinesfor preprocessing feature extraction and integration of time-series and spatial data

• Deploy and operationalizeAI/ML models and agentsas scalable services or APIs

• Implementmonitoring evaluation and validationfor both agent systems and ML models

• Visualize data and model outputs to support analysis and decision-making

• Collaborate with domain experts to integrate AI intoengineering and simulation workflows and document reusable solutions

Traits we believe make a strong candidate:

• Bachelorsdegree(minimum)inMechanical Engineering Computer Science or a related engineering discipline

• 13years of relevant work experience inAI ML software engineering or applied research roles(industry startup or research labs)

• Strong proficiency inPython programming

• Handson experience building agentic AI systemsthat includesmultistep task executionTool/function callingand workflow orchestration across agents or components

• Practical experience withmachine learning libraries including NumPy Pandas SciPy scikitlearn TensorFlow and/orPyTorch

• Ability to independently design build and debug endtoend AI workflows

Candidates with ademonstrable showcase projectwill be strongly preferred. Examples include (but are not limited to):

• An agentic AI system that automates a complex multistep task (engineering data analysis design or simulation related)

• A GitHub internal demo or portfolio project demonstratingagent orchestrationuse of tools/APIsnontrivial decision logic or reasoning loops

• Integration of LLM agents with data processing visualization or external software tools

The project doesnotneed to be simulationfocused but relevance to engineering workflows is a plus

• Experience withCFD or FEA workflows particularly involving geometry meshing or simulation postprocessingwill beconsidered as an advantage

• Familiarity withopensource engineering toolssuch asOpenFOAM SU2CalculiXor similarwill be considered as an advantage

Your success will be measured by:

• Effectiveness ofagenticAI andSciMLsystems in real workflows

• Quality scalability and maintainability of deployed AI systems

• Demonstrated impact in reducing manual effort and improving engineering workflows

• Ability to translate ambiguous physical systems problems into structured AI/ML solutions

• Strong collaboration across AI simulation and experimental teams