Job Overview
We are looking for an experienced hands-on Software Engineer to build automation, data analytics, and AI-assisted productivity solutions for Semiconductor Test Development workflows.
Key Responsibilities
Build Python-based scripts, automation tools, lightweight applications, dashboards, and data workflows for semiconductor test development use cases.
Design and perform testing/validation of developed tools, automation workflows, dashboards, and AI-assisted outputs to ensure reliability, accuracy, and maintainability.
Analyze engineering data, logs, test results, and workflow metrics to identify trends, anomalies, bottlenecks, and actionable insights.
Prototype AI-assisted tools, LLM-based applications, RAG/knowledge assistants, automation agents, or productivity solutions for engineering teams.
Work with engineers and stakeholders to understand open-ended problems, clarify requirements, iterate on prototypes, and document solutions for reuse.
Requirements
Bachelor's degree or equivalent experience in Electrical Engineering, Electronics Engineering, Computer Engineering, Computer Science, or a related technical field.
Strong programming skills, preferably in Python, with experience in scripting, automation, data processing, and practical tool development; C++ is a plus.
Experience with software testing and validation practices, including unit testing, integration testing, regression testing, and black-box/white-box testing as applicable.
Practical working knowledge of AI tools and concepts, including prompt engineering, LLM-based workflows, AI-assisted automation, AI agents, and retrieval-augmented generation systems.
Solid understanding of digital electronics fundamentals such as logic design, timing concepts, registers, buses, and basic hardware/software interaction.
Interest in data analytics, including the ability to explore datasets, identify patterns, and convert raw data into useful engineering insights.
Good communication, curiosity, ownership, and ability to work independently on ambiguous engineering problems.
Preferred
Experience building AI-assisted tools, LLM-based applications, RAG/knowledge assistants, automation agents, chatbots, or data-driven productivity solutions.
Experience with dashboards or analytics tools such as Power BI, Streamlit, Plotly, Dash, SQL, APIs, or data pipelines.
Exposure to semiconductor test, silicon validation, FPGA/ASIC workflows, ATE, bench validation, scan, MBIST, functional test, or hardware debug concepts is a plus.
Exposure to C, Verilog, VHDL, SystemVerilog, simulation outputs, or test pattern concepts is a plus.