Business Development Manager-Physical AI at Altera Corporation in San Jose, California, United States

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.

Responsibilities

• 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
• 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
• 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
• 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
• 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)
• Perception → planning → actuation pipelines
• Centralized vs distributed control architectures (robot, machine, and factory cell)
• Deterministic vs GPU-based processing trade-offs
• 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
• 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
• Provide structured market feedback to product management and engineering
• 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

Requirements

• Bachelor's Degree in Electrical Engineering, Computer Engineering, or related field (Master's preferred)
• Robotics, industrial / factory automation, autonomous systems, or edge AI / embedded systems
• Semiconductor, module, controls, or OEM environments
• 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)
• 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
• Understanding of 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)
• Robotics OEMs or integrators
• Industrial automation / controls / drive companies
• Autonomous-system, drone, or AMR/AGV developers
• Edge AI platform or appliance vendors
• MBA or business training is a plus

Skills

Required

• FPGA-based solutions
• Sensor fusion and perception pipelines
• High-speed I/O and memory subsystems
• ROS / ROS2
• AI frameworks
• Edge AI toolchains
• Encoder interfaces (BiSS, EnDat, SSI)
• MIPI CSI-2

Benefits

• 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.
• We use artificial intelligence to screen, assess, or select applicants for the position. Applicants must be eligible for any required U.S. export authorizations.