FPGA Engineer, LEO KMM FPGA

Amazon Leo is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities Create FPGA solutions to support LEO's satellite communication system. This is a unique opportunity to define a new system with few legacy constraints. The FPGA design engineer will work with systems teams to define/develop/implement/test/release FPGA based solutions to enable LEO. This will focus on creating digital designs for networking functions using the latest generations of FPGA technologies and modern FPGA design processes and tools. In this role you will: Have ownership of one or more FPGA bitstreams. - Create and release FPGAs through the development phases of uArchitecture-RTL Design-Physical Implementation-Timing Closure–Simulation Validation– Lab Based Silicon Validation Collaborate with network communication system architects to define and design/implement/test/release/support networking functions targeted to FPGA technology Collaborate with Digital Communications/Networking system architects and design engineers to implement digital logic functions in FPGAs. Collaborate with system architects and design engineers to implement digital logic functions in FPGA prototypes to validate/tradeoff architecture & design alternatives Collaborate with systems architects, HW engineering design teams & FW/SW design teams to bring up and test systems combining FPGA, firmware, RF, and Networking functions. Drive trade-off analysis to benefit customer experience and optimization of target technology resources for cost/size/power/performance/features