ATE Software Engineer

Description

About DriveNets

DriveNets is a leader in high-scale networking software for AI infrastructure and service providers. The company pioneered a disaggregated networking architecture that transforms the economics of large-scale networks while maximizing performance, utilization, and operational efficiency. DriveNets-powered networks are deployed by global leaders, including AT&T and Comcast, supporting more than 30% of total U.S. internet traffic. DriveNets AI Fabric delivers full-stack networking for AI infrastructures, providing the highest-performance, Ethernet-based alternative to InfiniBand. The solution is deployed by hyperscalers, NeoClouds, and enterprises worldwide. With over $1B raised, DriveNets continues to push the boundaries of modern networking infrastructure.

About The Role

We are seeking a senior ATE Software Engineer to design, build, and deploy our next-generation automated manufacturing test platform for advanced telecom, high-density switching, and optical networking hardware.

In this role, you will bridge the gap between R&D hardware/firmware teams and high-volume manufacturing lines. You will take ownership of ingesting, refactoring, and consolidating disparate R&D scripts, diagnostic tools, and legacy software into a single, scalable, production-grade test platform.

We expect you to leverage modern AI-assisted development tools and workflows to maximize engineering efficiency, accelerate delivery timelines, and build highly robust, self-healing test automation. You will deploy test stations across global Contract Manufacturers (EMS/ODM), actively stabilize production lines through bring-up and ramp-up, and drive continuous test maintenance and root-cause failure analysis (RCA).

Key Responsibilities

• Test Platform Architecture & Software Development:

Design, develop, and productize robust, modular test software frameworks for board-level (PCBA) and system-level manufacturing testing across multiple product lines and manufacturing sites.

• Codebase Unification & Refactoring:

Consolidate and standardize R&D diagnostic libraries, silicon validation scripts, and firmware tools developed across various environments (Python, C# / Visual Studio, VB, ATEasy, Linux) into a unified, maintainable test execution engine.

• AI-Accelerated Development & Workflow Automation:

Actively integrate Generative AI tools and AI coding agents into your daily workflow to accelerate code conversion/refactoring, automate test case synthesis, generate edge-case validation scripts, and enhance overall codebase resilience.

• Production Line Deployment & Stabilization:

Deploy test stations and fixtures to local and overseas EMS/CM production lines. Monitor, debug, and fine-tune test execution during NPI and ramp-up phases until yield, takt time, and test stability targets (CPK / First Pass Yield) are achieved.

• Failure Investigation & Intelligent RCA:

Investigate complex system-level and component-level test failures. Utilize advanced log analysis, structured telemetry, and pattern recognition to drive root-cause investigations and implement preventive software/hardware fixes.

• Ongoing Test Maintenance & Optimization:

Provide continuous operational Production line support and maintenance, bug fixes, software updates, and station cycle-time optimizations for active mass-production lines.

• R&D Collaboration & Test Specification:

Collaborate closely with Hardware, Firmware, and Validation teams during early design phases to define test specifications, drive Design for Testability,

• Documentation & Technical Reporting:

Author and maintain comprehensive testing documentation, Standard Operating Procedures (SOPs), test coverage matrices, and detailed failure analysis reports.

• Manufacturing Systems Integration:

Integrate automated test sequences with CM’s SFC/MES/QMS, serialized tracking, and central test log databases.

• Log Analysis & Analytics Tool Development:

Design and build dedicated log parsing, data visualization, and diagnostic analytics tools to streamline complex hardware/software debugging, accelerate root-cause analysis (RCA), and drive continuous production line cycle-time and yield optimization.

Requirements

• B.Sc. in Electrical Engineering, Software Engineering, Computer Science, or equivalent practical experience.
• 5+ years of hands-on experience in ATE software development and production test engineering for complex telecom, networking, or optical hardware products.
• Advanced, everyday practical mastery of AI-assisted engineering tools (e.g., GitHub Copilot, Cursor, LLM-based coding agents, automated prompt-driven refactoring) to radically accelerate code delivery, debug legacy systems, and enforce code quality.
• Strong software engineering skills in Python and Linux environments.
• Practical experience with test development in C# (.NET / Visual Studio), VB, or specialized test sequencers such as ATEasy.
• Proven track record of deploying, commissioning, and stabilizing ATE test benches at overseas tier-1 EMS/CM facilities.
• Strong grasp of digital and communication protocols (PCIe, I2C, SPI, MDIO, UART, Ethernet) and familiarity with lab equipment (oscilloscopes, power supplies, high-speed traffic generators).
• Strong analytical and debugging skills to isolate issues between hardware defects, firmware bugs, test software, and fixture/cabling failures.
• Experience writing clear engineering documentation, test procedures (SOPs), and technical root-cause reports.
• Excellent verbal and written English communication skills; readiness to support global manufacturing sites (including occasional international travel for line bring-up).
• Proven hands-on experience integrating ATE platforms and automated test tools with Contract Manufacturers MES, QMS, and Shop Floor Control (SFC) systems for automated serialization, unit routing, and quality data logging.

Preferred Qualifications

• Experience with high-density Ethernet switches, data center networking architectures.
• Hands-on experience testing high-speed optical transceivers and SerDes interfaces.
• Strong advantage: Practical knowledge of high-speed SerDes configuration, link-tuning, and signal integrity validation.
• Experience implementing AI/ML-driven log parsers, anomaly detection, or predictive yield analytics for manufacturing telemetry.
• Experience integrating JTAG / Boundary Scan tools (JTAG Tech’) into automated manufacturing flows.
• Familiarity with database architectures (SQL), data analytics, and SPC for production yield monitoring.