Software Engineer (AI & Data Analytics Automation)

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.