דרושים Sr Business Development Manager Amazon Electronics ב-אמזון ב-United States, Washington, Seattle

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
As a senior systems development engineer, you will work with a wide variety of functional groups and will be involved in the design and implementation of software systems for phased array antennas validation and test, as well as overall system integration:- Develop tools for characterizing antenna RF and system performance.
- Develop software and test rack automation to support production test stations.
- Support electrical and software bring-up, debug of new hardware.- Plan, develop and implement environmental test activities for phased array antennas.
- Implement DSP FPGA firmware to map high-level algorithms from Matlab or C to architecture-specific code.

- BS or MS in electrical engineering, computer engineering or computer science, or equivalent experience
- 5+ years of experience with C/C++ and Python or other scripting languages. Experience automating, building, and testing systems
- Experience with HW/SW bring up and debugging
- Experience working in a hardware lab with oscilloscopes, signal generators, power supplies, and other test equipment

- Solid fundamental CS / EE skill set with hands-on industry or university experience in embedded software development
- Knowledge of FPGA systems, GPIO/I2C/SPI and peripheral interfacing.
- Experience with RTL and FPGA development tools
- Experience with Matlab or tools alike
- Knowledge of Database systems

You: As a Sr. Machine Learning Compiler Engineer III on the AWS Neuron team, you will be a thought leader supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads. Architecting and implementing business-critical features, publish cutting-edge research, and mentoring a brilliant team of experienced engineers excites and challenges you. You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects. A background in Machine Learning and AI accelerators is preferred, but not required.Work/Life Balance
Mentorship & Career Growth

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team

- Bachelor's degree in computer science or equivalent

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.The Senior Electric Propulsion Engineer will provide technical leadership within Kuiper's Propulsion Design Engineering team as a subject matter expert for the electric propulsion system. This position demands a combination of technical depth, leadership abilities, and systems engineering experience capable of driving innovation of spacecraft propulsion technologies that ultimately enable customer service via the Kuiper satellite constellation. In this role, you will advise test, manufacturing, and mechanical engineers on electric propulsion best practices. Your expertise will directly influence all aspects of propulsion system design and development, including propellant storage and delivery, magnetic circuit design, cathode design, propulsion system architecture, avionics requirements, thermal management, embedded software design, and in-flight concepts of operation (CONOPs).
Key job responsibilities
The Senior Electric Propulsion Engineer supports the system and design throughout the hardware development lifecycle, from conception, prototyping, design validation & test, through production manufacturing, and flight operations. Key responsibilities will include
- impact and influence the full scope of propulsion system design, development, and production including: propellant storage and delivery; thruster magnetic circuit design; cathode design; overall system architecture trades; Propulsion avionics requirements; thermal management; system integration; and propulsion embedded software
- perform detailed system performance and risk analyses to support design trades, risk assessments, and risk mitigation plans
- act with delegated design authority to approve: production non-conformances; changes in design, test, and systems engineering artifacts; and Concepts of Operations for the Kuiper Propulsion system
- identify and assess technical risks based on data and outcomes in development, production, and flight operations
- lead or support test execution for development, validation, and risk assessments - especially for integrated tests across multiple large vacuum chambers suitable for testing Hall effect thrusters
- define test plans & test requirements to meet development and production test objectives
- define procedures for in-flight responses to novel off-nominal scenarios, and directly support flight operations as neededA day in the life
The Senior Electric Propulsion Engineer will work within multi-disciplinary teams as the go-to source for electric propulsion knowledge. Teams will work on all aspects of propulsion system development, implementation and production and will require you, as propulsion expert, to ensure the key aspects of device operation are being properly considered and tested within constraints. You will aid in test planning, operation and data analysis, co-author test reports and disseminate impactful results.

- Bachelor's degree in mechanical engineering, electrical engineering, material science, physics or equivalent, or Bachelor's degree and 5+ years of professional or military experience
- 5+ years of experience with electric propulsion technologies through design or test

- Master's degree or above in Electrical Engineering, Mechanical Engineering, or a related field
- 7+ years of developing electric propulsion technologies through design & test cycles
- Experience with Design of Experiments (DOE)
- Familiarity with electric circuit design
- Experience with finite element analysis for electromagnetic fields and/or fluid flow

Prime Air is seeking an experienced Supply Chain Engineer who combines technical and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively. We’re looking for people who innovate and love solving hard problems. You will work hard, have fun, and of course, make history!As a Senior Supply Chain Engineer within Amazon Prime Air, you will lead supplier performance and manufacturing readiness across multiple product lines. You will drive scalable mechanisms that improve quality, cost, and delivery, while influencing sourcing strategy, design decisions, and supplier capability. Partnering closely with engineering, quality, and operations, you will enable suppliers to achieve rate, yield, and reliability targets—balancing Day 1 agility with the structure needed to scale Prime Air’s hardware production globally.Key job responsibilities
- Define supplier performance strategy across Prime Air programs—driving quality, cost, and delivery improvements through scalable mechanisms and structured governance.- Influence design, sourcing, and manufacturing strategies through data-backed should-cost models and capability insights, shaping long-term supply decisions.- Lead multi-supplier readiness and rate-scaling initiatives, ensuring alignment to roadmap, capacity, and launch objectives across product lines.- Govern complex technical changes and manufacturing validations, ensuring design intent, reliability, and rate readiness across multiple suppliers.- Own cross-functional program integration, coordinating engineering, quality, and operations deliverables to ensure synchronized ramp and readiness milestones.- Establish global supplier health and risk frameworks, driving standardization, visibility, and accountability across the supply base.- Drive systemic improvement programs that eliminate recurring issues and raise overall supplier maturity.- Act as a technical and operational leader, representing SCEO in strategic reviews and influencing Prime Air’s manufacturing and sourcing roadmap.A day in the life
Each day blends Day 1 innovation with disciplined execution. You’ll shift between solving urgent supplier issues, building scalable mechanisms, and aligning hardware production across teams. One hour you’re deep in yield data or a cost model; the next, you’re on the factory floor driving readiness. This role thrives in ambiguity—turning chaos into structure, and structure into scalable systems that deliver quality, cost, and schedule at speed.

- Experience in developing functional specifications, design verification plans and functional test procedures
- 5+ years of electrical or mechanical engineering experience
- Travel up to 50% domestic travel with short notice
- Proven leadership in supplier relationship management, including defining and governing SLAs, performance scorecards, and escalation mechanisms across multiple suppliers or programs.
- Exceptional written and verbal communication skills, with demonstrated ability to influence senior leaders, align cross-functional teams, and represent Supply Chain Engineering in executive and supplier forums.
- Ability to operate with high autonomy in a global environment, including leading onsite supplier engagements and executive reviews with minimal direction

- Master's degree in electrical engineering, computer engineering, or equivalent
- Experience working with interdisciplinary teams to execute product design from concept to production
- Experience in component selection and understanding of component reliability
- 7+ years of experience in supplier management or manufacturing engineering for aerospace, automotive, robotics, or high-precision hardware.
- Expertise developing and governing should-cost models, using cost analytics to influence design strategy, sourcing decisions, and long-term negotiation frameworks.
- Deep understanding of DFM/DFA principles and advanced manufacturing quality tools (PPAP, PFMEA, control plans, process validation), with demonstrated ability to standardize and deploy them across diverse supplier networks.

This function will Accelerate the Applied AI Solutions GTM strategy and growth (as defined by our Operating Plan) through strategic initiatives that transform our organizational capability and operational excellence. This position requires a strong understanding of the internal AWS and external Partner business dynamics, AWS field enablement and planning processes, the ability to make important data-driven decisions, and bias for action to implement strategies that enhance performance with speed.Key job responsibilities
Contribute to AAIS portfolio strategy development, architecting comprehensive strategies and analytics frameworks to drive data-driven decision making across regions.Design and implement field and partner enablement programs, including training, and engagement models to transform sales effectiveness through innovative technology solutions.Partner cross functionally to develop and maintain measurement frameworks to evaluate initiative and program effectiveness.Develop geo-specific GTM plans and "Get to Green" plans, implementing scalable mechanisms that drive organizational effectiveness across multiple regions.Build strategic relationships with field and partner leadership, serving as a primary liaison between AAIS GTM leaders and regional stakeholders.Foster organizational alignment through effective communication of strategy and goals across all levels, driving proven results.Roll up sleeves and build sophisticated data models and data analysis as needed.
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 5+ years of developing, negotiating and executing business agreements experience
- Bachelor's degree
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience with sales enablement platforms

- Experience interpreting data and making business recommendations
- MBAPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

As the Sr. SDM for the Inference Technology Team, you will lead a strong team of managers and engineers to build fundamental inference technology building blocks and libraries to enable AI developers to optimize model for inference on Trainium and Inferentia devices. You will be responsible for the full development life cycle of inference library and feature development, including reliability and scalability. You will develop the Neuronx_Distributed Inference Libraries and contribute to other popular open source Inference Libraries, enabling customers to optimize LLMs, multimodal, and generative models.A day in the life
You will work with the executive leadership and other senior management and technical leaders to define product directions and deliver them to customers. We build massive-scale distributed training and inference solutions, developing the full stack of software, servers and chips together with teams across the Annapurna organization to run the largest machine learning workloads.Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Work/Life Balance
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

- 10+ years of engineering experience
- 5+ years of engineering team management experience
- 10+ years of planning, designing, developing and delivering consumer software experience
- Experience partnering with product or program management teams
- Experience managing multiple concurrent programs, projects and development teams in an Agile environment

- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Research new and innovative machine learning approaches.

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.