Business Development Manager – Physical AI

Key Responsibilities

• Identify and prioritize target segments including robotics: industrial and collaborative robots (cobots), autonomous mobile robots (AMR/AGV), humanoids, end-of-arm tooling
• Autonomous systems: drones / UAVs, autonomous ground and off-road vehicles, autonomous material handling
• Industrial and factory automation: PLC / PAC controllers, motion and servo-drive control, machine control, IIoT / edge gateways
• Edge AI: edge AI appliances and gateways, smart cameras and sensors, on-premise inference platforms
• Track and interpret trends in edge AI and on-device inference (model deployment, quantization, AI acceleration)
• Multi-sensor fusion (camera, LiDAR, IMU, force / torque)
• Real-time deterministic control, multi-axis motion, and industrial networking convergence (fieldbus → TSN)
• Industry 4.0 / IIoT, predictive maintenance, and the software-defined factory
• Robotics and autonomy software stacks (ROS / ROS2) and AI frameworks
• Identify opportunities where customers require deterministic, low-latency control and motion loops
• High-throughput, low-power edge AI inference
• Multi-sensor aggregation and time synchronization
• Functional safety for human-machine collaboration
• Reconfigurability across evolving platforms and long industrial lifecycles
• Build relationships with robotics OEMs, industrial-automation vendors (controls, drives, machine builders), autonomous-system developers, edge AI platform vendors, module / subsystem suppliers, and system integrators
• Drive early-stage engagement with sales to influence system and safety architecture decisions
• Position FPGA-based solutions across control, sensing, networking, and edge AI systems
• Secure design-ins across platforms, machines, and derivatives
• Support technical sales discussions spanning: Motor / motion control (field-oriented control, multi-axis servo, encoder interfacing), Industrial control and real-time networking (PLC / PAC, EtherCAT, PROFINET, EtherNet/IP, TSN), Sensor fusion and perception pipelines, Edge AI / ML inference (CNN- and transformer-based workloads), Functional-safety implementation (safe motion, redundancy, diagnostics)
• Engage in system-level discussions involving perception → planning → actuation pipelines, Centralized vs distributed control architectures (robot, machine, and factory cell), Deterministic vs GPU-based processing trade-offs
• Build and manage relationships with sensor, encoder, and actuator / drive vendors, Industrial networking, controls, and automation-software vendors, IP providers and software / AI stack vendors (ROS ecosystem, vision / AI frameworks), Robotics and automation module makers, ODMs, and system integrators
• Enable joint solutions and reference designs to accelerate customer adoption
• Develop high-impact sales collateral including solution briefs, reference architectures (motion control, industrial networking, sensor fusion, edge AI), competitive positioning vs FPGA / SoC / ASSP / GPU / MCU alternatives, and ROI / TCO analyses
• Support sales teams with use-case-driven messaging for robotics, autonomous systems, industrial automation, and edge AI applications, Customer presentations and technical positioning, Opportunity qualification and deal progression, Deliver presentations at customer meetings, industry events, and trade shows
• Internal collaboration: Provide structured market feedback to product management and engineering, Influence product direction based on customer needs related to: Real-time I/O and deterministic networking, Motion-control and safety features, Edge AI capabilities and AI fabric, Power, thermal, and form-factor for embedded, mobile, and industrial deployment, Support pricing discussions and business case development

Qualifications

• Bachelor's Degree in Electrical Engineering, Computer Engineering, or related field (Master's preferred)
• 7+ years of experience in: Robotics, industrial / factory automation, autonomous systems, or edge AI / embedded systems
• Semiconductor, module, controls, or OEM environments
• Strong understanding of motion / motor control and real-time systems
• Industrial control and networking concepts
• Sensor technologies and fusion (camera, LiDAR, IMU, force / torque)
• AI / ML fundamentals (edge inference pipelines)
• Familiarity with key interfaces and networks: EtherCAT, PROFINET, EtherNet/IP, TSN, real-time Ethernet, Encoder interfaces (BiSS, EnDat, SSI), MIPI CSI-2
• Experience engaging global customers and managing long design cycles
• Experience with FPGA-based systems or FPGA solution selling
• Familiarity with high-speed I/O and memory subsystems, multi-axis motion control, and edge AI deployment constraints (latency, power, form factor)
• Familiarity with ROS / ROS2, AI frameworks, and edge AI toolchains
• Awareness of functional-safety and industrial standards (ISO 10218, ISO/TS 15066, IEC 61508 / SIL, IEC 61131-3, IEC 62443)

Critical Success Factors

• Design-in mindset: Ability to engage early and secure long lifecycle platform wins
• System-level thinking: Understanding the complete signal chain from sensing through processing to actuation
• Execution focus: Ability to convert opportunities into pipeline and revenue
• Customer-centric approach: Strong listening skills and ability to translate requirements into solutions
• Ecosystem leverage: Driving wins through partnerships, not just silicon features