Director of Engineering, AI Transformation

About Inter Digital Inter Digital is a global research and development company focused primarily on wireless, video, artificial intelligence ("AI"), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming.

As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies.

Founded in 1972, Inter Digital is listed on Nasdaq. Inter Digital is a registered trademark of Inter Digital, Inc. For more information, visit:

The Role Lead the engineering function inside Inter Digital’s AI Transformation team. Set technical direction, own delivery against the plan, and manage and build the team that delivers it.

The Team Our AI Transformation team applies AI to how Inter Digital works. It is a small group of engineers and product managers operating close to the business, with a mandate that runs company-wide. This role leads the engineering side of it and reports to the Vice President, Strategy and AI Transformation.

• Own the architecture and engineering platform.
• Define the technical architecture, platform capabilities, shared services, interfaces and engineering standards the team builds on.
• Make deliberate choices about what belongs in reusable infrastructure versus individual applications.
• Translate business requirements into technical systems.
• Work with product management to turn business needs and workflow requirements into scalable technical approaches.
• Understand the capabilities and constraints of the infrastructure, challenge assumptions where needed, and identify the simplest architecture that can reliably meet the requirement.
• Anticipate engineering constraints and failure modes.
• Identify scaling, integration, data-access, security, reliability, latency, model, cost and maintainability issues early.
• Surface technical tradeoffs before they become delivery problems and design around constraints rather than discovering them after implementation.
• Manage and build the team.
• Lead the engineering team and grow it to the size and shape the plan requires.
• Own hiring, onboarding, development and retention, including the technical career paths that keep strong engineers here.
• Own delivery.
• Turn product priorities into executable engineering plans.
• Decompose work, size it, identify dependencies, commit to dates and surface risks or slips early.
• Maintain a clear view of what the team can deliver and what is constraining it.
• Create engineering leverage.
• Expand the team's capacity by building scalable practices and thoughtfully leveraging resources.
• Establish effective use of AI-assisted development, reusable components, shared infrastructure, automation and engineering practices that compound across projects.
• Own the engineering side of build versus buy.
• Supply what it costs to build, buy, and run, and hold the team to the answer.
• Nothing gets built here that a foundation model API or an existing service already does well.
• Build the measurement: the evaluation harness and instrumentation needed to measure quality, usage, latency, reliability, and cost in production.
• Set priorities and stretch them.
• Sequence the work with product management, then deliver more against that plan than the headcount predicts through sharper tooling, reusable building blocks and a cohesive team.
• Work inside enterprise constraints.
• Data classification, information security review and sanctioned tooling are real limits here.

• 8+ years building software, including 5+ years leading engineers with meaningful technical and people‑management responsibility.
• Demonstrated ownership of architecture and technical direction for production software systems, preferably in a small or rapidly evolving engineering environment.
• Strong systems intuition: able to move from an ambiguous business…