GDL Lab Engineering Manager

Description

Are you ready to influence and shape the future of semiconductor validation?

TI is looking for a visionary Lab Engineering Manager to lead a high-impact, multi-vector engineering organization. This is not a traditional lab management role; you will be the technical and strategic engine driving efficiency, automation, and cutting-edge technology across the entire company. As a leader in this central team, you will bridge the gap between hardware excellence and software intelligence, influencing business units across Analog and Embedded to redefine how TI validates the next generation of technology.

About the job:

• Lead & Innovate: Guide and define the direction for validation technology, creating innovative, reusable hardware and software solutions that scale across multiple business units

• Collaborate & Influence: Work as a key execution partner with the Business Units, validation/test councils, TTS, IT and other orgs to align lab engineering with TI’s long-term product strategy

• Drive Scalability: Move beyond simple support to create "low cost of ownership" solutions that are remote-capable, compact, and designed for high-volume, high-impact deployment

Impact you will make:

• Software Infrastructure & Frameworks: Lead the evolution of the validation community’s digital backbone; you will oversee the development and scaling of common software infrastructure, transitioning the community toward modern, high-throughput frameworks using Python and maintaining robust LabVIEW/TestStand environments

• Operational Excellence & Tooling: Own the roadmap for operational tools and processes; you will drive the "Smart Lab" vision—implementing intelligent solutions for asset management, equipment utilization, and automated tracking to make the entire GDL organization more operationally efficient in bench and test environments

• Key Technology Vector Leadership: Act as the primary enabler for TI’s most critical testing requirements; you will lead the deployment of specialized setups and platforms that empower teams to tackle complex challenges in EMC/EMI, space radiation, and data center testing

• AI Strategy & Digital Transformation: Serve as the AI strategy driver for the validation community; you will lead the integration of AI/ML into the lab loop—from developing agentic bench platforms to implementing advanced data analytics—creating opportunities to influence AI adoption across the entire company

Responsibilities include:

• Building the digital and physical infrastructure that defines the future of TI validation

• Leading the transition toward AI-augmented engineering and high-throughput automation

• Scaling specialized testing capabilities (EMC, Space, Data Center) across our global footprint

• Optimizing how we work by turning complex operational challenges into streamlined, automated processes

Qualifications

Minimum Requirements:

• 5+ years of experience in semiconductor validation, test, or application support

• 5+ years of experience in automated software development

• Proven expertise in designing and deploying fully automated bench validation platforms (integrating hardware, software, and instruments)

• Strong understanding of analog and mixed-signal circuits and advanced lab instrumentation

• Exceptional system-level debugging skills and a "big picture" thinker capable of influencing cross-functional stakeholders

• A passion for driving broad, scalable impact within a complex, global organization

Preferred Qualifications:

• Experience managing engineering teams

• Advanced programming: Proficiency in Python and experience with LabVIEW and TestStand

• Specialized standards: Intimate knowledge of EMC testing standards (CISPR 25, 32, IEC ESD, etc.) and space radiation testing

• Data intelligence: Experience developing advanced data analytics using Spotfire, post-processing algorithms, or ML-driven tools

• AI fluency: Proven ability in emerging AI technologies; you possess the technical intuition to move from standard automation to AI-augmented engineering, utilizing LLMs, prompt engineering and machine learning to solve complex validation, test and data challenges

• Domain expertise: Knowledge of functional/system-level testing for Automotive and Industrial segments