Engineer I Artificial Intelligence

**Job Title:** Engineer I, Artificial Intelligence **Job Description:** **The Role:**  The mission of this role is to **design, develop, deploy, and operationalize agentic AI systems and scientific machine learning solutions** that automate complex, multi-step technical workflows.  The AI Engineer will focus on building **LLM-driven, goal-oriented AI agents** and **data-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 about **agentic 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 develop **agentic AI systems** for multi-step reasoning, tool usage, and workflow orchestration   * Build **LLM-driven workflows and Python-based pipelines** integrating agents with data, APIs, and engineering tools   * Develop and apply **scientific machine learning models** using experimental, sensor, and simulation data   * Create **data pipelines** for preprocessing, feature extraction, and integration of time-series and spatial data   * Deploy and operationalize **AI/ML models and agents** as scalable services or APIs   * Implement **monitoring, evaluation, and validation** for both agent systems and ML models   * Visualize data and model outputs to support analysis and decision-making   * Collaborate with domain experts to integrate AI into **engineering and simulation workflows**, and document reusable solutions  **Traits we believe make a strong candidate:**  * Bachelor’s degree (minimum) in **Mechanical Engineering, Computer Science, or a related engineering discipline**  * 1–3 years of relevant work experience in **AI, ML, software engineering, or applied research roles** (industry, startup, or research labs)  * Strong proficiency in **Python programming**  * **Hands**‑**on experience building agentic AI systems that includes** multi‑step task execution, Tool/function calling and workflow orchestration across agents or components  * Practical experience with **machine learning libraries**, including NumPy, Pandas, SciPy, scikit‑learn, TensorFlow and/or PyTorch  * Ability to independently design, build, and debug end‑to‑end AI workflows  Candidates with a **demonstrable showcase project** will be strongly preferred. Examples include (but are not limited to):  * An agentic AI system that automates a complex multi‑step task (engineering, data analysis, design, or simulation related)  * A GitHub, internal demo, or portfolio project demonstrating, agent orchestration, use of tools/APIs, non‑trivial decision logic or reasoning loops  * Integration of LLM agents with data processing, visualization, or external software tools  The project does **not** need to be simulation‑focused, but relevance to engineering workflows is a plus  * Experience with **CFD or FEA workflows**, particularly involving geometry, meshing, or simulation post‑processing will be considered as an advantage  * Familiarity with **open**‑**source engineering tools** such as OpenFOAM, SU2, CalculiX or similar will be considered as an advantage  **Your success will be measured by:**  * Effectiveness of agentic AI and SciML systems 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