Lead AI Architect & Hands-on Engineer

Edison Smart®; Austin (TX); Remote; USD 180,000 - 240,000; Full time

Job summary

Edison is developing advanced AI software for decision support in complex environments. We seek a Principal AI Engineer to own the AI architecture while remaining hands-on, shaping technical direction from design to production.

You will lead systems that fuse data from multiple sources, develop models for perception, tracking and multimodal reasoning, and drive production-ready pipelines with a focus on latency, scalability and reliability.

Qualifications

• Experience owning AI architecture for production systems.
• Background in Physical AI, robotics or real-world AI applications.
• Elite experience in computer vision, tracking, sensor fusion, multimodal AI.

Responsibilities

• 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 perception, tracking and multimodal reasoning.
• Design pipelines and software components to move AI into production.
• Remain hands on with coding, prototyping, testing and performance optimisation.
• Make key decisions on system design, inference, latency, scalability and reliability.
• Collaborate across AI, software and systems engineering to deliver integrated solutions.
• Establish sound engineering practices and help shape foundations as the business grows.

Skills

AI architecture

Production AI systems

Computer vision

Robotics/physical AI

Real-time processing

System design

Inference optimization

PyTorch

TensorFlow

Tools

PyTorch

TensorFlow

Job description

Edison is developing advanced AI software for decision support in complex environments. We seek a Principal AI Engineer to own the AI architecture while remaining hands-on, shaping technical direction from design to production.

You will lead systems that fuse data from multiple sources, develop models for perception, tracking and multimodal reasoning, and drive production-ready pipelines with a focus on latency, scalability and reliability.