Business Development Manager – Physical AI

Job description

Job Details: Job Description: We are seeking a Business Development Manager to drive growth in FPGA-based solutions across the Physical AI domain – spanning robotics, autonomous systems, industrial and factory automation, and edge AI. This role focuses on expanding design wins across intelligent machines that sense, decide, and act in the physical world, from collaborative robots and autonomous platforms to factory-automation controllers and edge AI appliances. You will act as the bridge between customers, product management, engineering, and ecosystem partners to position FPGA solutions against competing architectures including ASSPs/SoCs, GPUs, and microcontroller-based platforms. Physical AI is converging perception, decision, and actuation onto real-time machines while pushing more intelligence to the edge, and industrial automation is moving toward connected, software-defined, and AI-enabled factories. FPGAs are uniquely positioned to unify deterministic control, sensor fusion, real-time networking, and edge AI inference on a single adaptable platform. As several of these markets are fast-emerging, the role includes helping establish and scale the market motion – which requires strong technical business leadership at the system level. Key Responsibilities 1. Market Development & Strategy 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 2. Customer Engagement & Design Wins 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 3. Ecosystem & Partnerships 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 4. Sales Enablement & Execution 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 5. 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 The pay range below is for Bay Area California only. Actual salary may vary based on a number of factors including job location, job-related knowledge, skills, experiences, trainings, etc. We also offer incentive opportunities that reward employees based on individual and company performance. $166.9K - $241.6K USD We use artificial intelligence to screen, assess, or select applicants for the position. Applicants must be eligible for any required U.S. export authorizations. Qualifications: Required 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