We are seeking a Business Development Manager to drive growth in FPGA-based solutions across the ... Robotics and autonomy software stacks (ROS / ROS2) and AI frameworks Identify opportunities where ...
We are seeking a Business Development Manager to drive growth in FPGA-based solutions across the ... Robotics and autonomy software stacks (ROS / ROS2) and AI frameworks Identify opportunities where ...
OR · On-site
$180K - $240K/yr
Mission management frameworks such as behavior trees, hierarchical task networks, state machines ... Experience with ROS, DDS, or similar middleware for robotics/autonomy systems. * Experience with ...
OR · On-site
$180K - $240K/yr
Mission management frameworks such as behavior trees, hierarchical task networks, state machines ... Experience with ROS, DDS, or similar middleware for robotics/autonomy systems. * Experience with ...
Manager Ros Robotics information
What is the difference between Manager Ros Robotics vs Robotics Engineer?
| Aspect | Manager Ros Robotics | Robotics Engineer |
|---|---|---|
| Required Credentials | Bachelor's or Master's in Robotics, Engineering, or related field; leadership experience | Bachelor's or Master's in Robotics, Mechanical, Electrical Engineering, or Computer Science |
| Work Environment | Oversees teams in labs, manufacturing, or R&D facilities; managerial duties | Designs, develops, and tests robotic systems; hands-on technical work |
| Employer & Industry Usage | Used in robotics companies, manufacturing, automation firms | Employed in similar industries, focusing on technical development |
| Common Search & Comparison | Often compared for leadership roles in robotics | Compared for technical expertise and development roles |
The main difference between Manager Ros Robotics and Robotics Engineer lies in their focus: the Manager oversees teams and project management, requiring leadership skills, while the Robotics Engineer concentrates on designing and developing robotic systems with technical expertise.
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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 ona number offactors 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- $241.6KUSD
We use artificial intelligence to screen, assess, or select applicants for the position.Applicants must be eligible for any required U.S. export authorizations.
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
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
Preferred Qualifications
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)
Prior experience with:
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
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
KPIs / Success Metrics
Design wins and revenue growth across robotics, autonomous systems, industrial automation, and edge AI segments
Number of qualified opportunities identified in motion control, industrial networking, sensor fusion, and edge AI systems
Pipeline growth and forecast accuracy
Engagements with OEMs, automation vendors, module vendors, and system integrators
Contribution to sales enablement and deal progression
About Altera
Sourced by ZipRecruiter
Company size
1,001 - 5,000 Employees
Headquarters location
San Jose, CA, US
Year founded
1983