Principal AI Engineer

Principal AI Engineer
Applied AI and Autonomous Systems
Location: Austin, TX preferred (remote considered)
Edison is working with a VC backed, defense focused technology company who are developing advanced AI software that brings together data, intelligent models and connected systems to support decision making in complex, real world environments.
The engineering team are focused on turning AI capabilities into reliable, deployable products, working across perception, data processing, autonomous systems and real time intelligence.
They are looking for a Principal AI Engineer to take ownership of the AI architecture while remaining fully hands on with the engineering. This is an opportunity to shape the technical direction of a growing platform, solve challenging system-level problems and take ideas from initial design through to production.
The Role
Own the architecture and technical direction of AI capabilities across the platform.
Design and build systems that combine data from multiple sources to produce reliable, useful intelligence.
Develop and integrate AI models across computer vision, perception, tracking and multimodal reasoning.
Design the pipelines and software components required to move AI capabilities into production.
Remain hands on with coding, prototyping, implementation, testing and performance optimisation.
Make key decisions around system design, model selection, inference, latency, scalability and reliability.
Work across AI, software and systems engineering to deliver integrated solutions in demanding operational environments.
Establish sound engineering practices and help shape the technical foundations as the business grows.
Background Needed:
Strong experience building and deploying production AI systems, with the ability to own architecture as well as implementation.
A background in the Physical AI space, robotics, autonomous systems or other applications where AI interacts with the real world.
Elite level experience in as computer vision, object tracking, sensor fusion, multimodal AI, vision language models or LLM-based reasoning.
An understanding of how models, data pipelines, software infrastructure and connected systems fit together.
Familiarity with real time processing, inference optimisation and deployment across distributed environments.
The ability to move between high level system design and detailed engineering, making pragmatic decisions and delivering working solutions.
Comfortable in an early stage environment where ownership is high, priorities evolve and engineers have a direct influence on the product.
The Opportunity
Join a growing, VC backed defense tech business at an important stage of its development.
Take meaningful ownership of the AI architecture and influence the direction of the platform.
Work on complex AI challenges with applications beyond traditional software environments.
Remain close to the engineering while helping establish the foundations for future growth.
Have the autonomy to make technical decisions and see your work through to deployment.
If you're a hands on AI engineer who enjoys owning complex systems from architecture through implementation, please apply here to tee up a conversation. Must be a U.S. person as defined under ITAR.

Work arrangement
Yes