Physical AI Solutions Architect

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Job Description:

Job Description

We are seeking a Physical AI Solutions Architect to lead the design and delivery of next-generation robotics, drones, medical, industrial and quantum compute systems that combine AI, real-time control, and heterogeneous compute (CPU/GPU/FPGA).

This role is responsible for defining end-to-end system architectures, driving customer engagements and PoCs, and translating advanced Physical AI concepts into production-ready solutions.

The ideal candidate bridges sense-think-act physical AI pipeline, and hardware acceleration, with a strong focus on low-latency, deterministic, and scalable systems deployed in real-world environments.

Key Responsibilities

• End-to-End Physical AI System Architecture. Define full-stack architectures spanning sensors, perception, localization, planning, control and actuation. Design Sense-Think-Act pipelines with strict latency and determinism constraints. Evaluate hardware/software partitioning, especially CPU vs GPU vs FPGA mapping
• Customer Engagement & Solution Delivery: Lead technical engagements with physical AI customers. Translate customer requirements into architecture proposals and solution roadmaps and deliver:
  • Technical presentations and executive briefings
  • System-level design recommendations
  • Competitive positioning vs GPU/CPU alternatives
• Proof-of-Concept (PoC) & Prototyping: Drive PoC development to validate architecture and performance, and work with engineering teams to build demos
• Physical AI Strategy & Market Development:
  • Analyze physical AI market trends, customer needs, and competitive landscape
  • Define physical AI solution stack (hardware + software + middleware)
  • Reference architectures for key segments
• Contribute to white papers, technical blogs, and training materials

Qualifications:

• Must have BS/MS, PhD preferred in Robotics, Electrical Engineering, Computer Engineering, Computer Science, or related field.
• 10+ years' experience in physical AI including robotics, drones, AI systems, or solutions architecture
• Strong expertise in one or more domains: Robotics systems and AI/ML for robotics.
• Experience with:
  • ROS / ROS2
  • FPGA platforms (RTL, HLS) - Preferred, but not mandatory
  • Real-time control systems and deterministic processing
  • E2E robotics control loop architecture
  • World modeling and point cloud generation
  • Motion planning
  • Physical AI SDK
• Familiarity with:
  • Sensor fusion, localization, motion planning, control loops
  • VLA and VLM models

Travel Requirements: 30%

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