AI Automation Design Packaging Lead - TX, Austin, United States
Originally posted 6 July 2026 by the employer.
Lead AI workflow development and packaging design automation across substrates, organic interposers, and bridge interconnects.
About the role
This role leads a team in the development and deployment of packaging design automation and AI-driven workflows. The work focuses on substrates, organic interposers, and bridge interconnects for advanced heterogeneous integration.
What you'll do
- Drive the development, deployment, and maintenance of AI workflows for substrate, interposer, and silicon bridge design methodologies. - Deploy AI/ML methodologies to optimize critical design stages, including auto-routing, component placement, and signal integrity optimization. - Collaborate with EDA vendors and internal stakeholders to define and implement feature roadmaps for 2.5D and 3D packaging. - Lead the transition from manual design practices to agentic and algorithmic design operational models. - Coordinate with electrical and mechanical analysis teams to build closed-loop optimization systems feeding simulation results back into design construction. - Prepare and present executive summaries of automation ROI, efficiency gains, and tool capability advancements while coordinating tape-outs and mentoring junior engineers.
What you'll need
- Bachelor or MS degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field with relevant packaging experience. - Technical background bridging physical design requirements and software automation to generate AI-driven workflows. - Experience translating complex design challenges into scriptable, scalable workflows across Design, EDA, and AI teams. - Technical leadership experience guiding design tape-outs and packaging methodology milestones.
Nice to have
- Knowledge of EDA packaging design tools such as Cadence APD/SIP, Siemens Xpedition, or Synopsys 3DIC/Compiler. - Proven track record of developing automation using Python, Tcl, SKILL, or C++. - Experience applying AI/ML frameworks such as PyTorch or TensorFlow to engineering or design problems. - Familiarity with advanced packaging architectures, including 2.5D/3D, chiplets, fan-out, and hybrid bonding. - Familiarity with design verification flows (DRC/LVS) and electrical extraction concepts.
Skills: AI-Driven workflows, advanced heterogeneous integration, packaging design automation, 2.5D and 3D packaging, substrate, interposer, silicon bridge