Annapurna Labs (U.S.) Inc.

The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. AWS Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at AWS. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations.The AWS Neuron team works to optimize the performance of complex neural net models on our custom-built AWS hardware. More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, the team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in performance.You: Machine Learning Compiler Engineer II on the AWS Neuron team, you will be 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 contributing to 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.About the teamAbout UsInclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.BASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of experience architecting and optimizing compilers- Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python ...

Amazon Web Services (AWS) internships are full-time (40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.In Annapurna Labs we are at the forefront of hardware co-design not just in Amazon Web Services (AWS) but across the industry. The work we do is cutting-edge and internet-scale while also being deeply important to our customers. We design and build every component of our hardware and software to come together into products that our customers use for accelerated computing through Machine Learning acceleration and FPGA acceleration. If you are interested in "building a complete product" from inception to delighted customers, Annapurna is a fantastic choice.If this sounds exciting to you - come build the future with us!As a member of the Machine Learning Acceleration team you will be responsible for defining and checking the specification of critical hardware modules using formal methods and industrial model checkers. You will be a part of a world class pre-silicon hardware design team. The job entails understanding requirements of specific hardware blocks and writing functional descriptions of correct behavior. Specifications are written in hardware description languages like Verilog and System Verilog Assertions (SVA). Using industrial model checkers you will then learn techniques for proving the hardware being designed matches the modeled specification. Advances proof techniques, such as modeling abstractions, and inductive reasoning will be utilized. Automation techniques and scripting flows are also leveraged to accelerate proof techniques. Mentorship & Career GrowthOur team is dedicated to supporting new team members in an environment that celebrates knowledge sharing and mentorship. Projects and tasks are assigned in a way that leverages your strengths and helps you further develop your skillset.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life HarmonyOur team puts a high value on work-life harmony. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility and encourage you to find your own balance between your work and personal lives.BASIC QUALIFICATIONS- Currently enrolled in a Bachelor’s degree program or higher in Electrical Engineering, Computer Engineering, Computer Science or related fields with a graduation conferral date between December 2025 and September 2026- Completed coursework or prior internship experience with formal methods (SW/HW)- Coursework or prior internship experience in the basics of computer architecture. ...

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.The AWS Cloud Storage offers a complete range of hardware and software for customers to store, access, govern, and analyze their data, reducing costs, increasing agility, and accelerating innovation.AWS Cloud Storage team is hiring firmware engineers with a background in NVMe memory devices to solve our customers toughest problems.As a firmware engineer on the AWS Cloud Storage team, you will be a thought leader at the forefront of consumer storage and networking solutions. You should feel equally comfortable in server and embedded environments, possess a deep understanding of computer architecture, Linux OS, and programming sophisticated embedded devices.Every day you will be working alongside brilliant engineers and leaders who obsess about performance, availability, scalability and durability of customer data, with the ambitious goal of improving AWS' industry-leading product.Key job responsibilities- Research, design, implement Firmware to support NVMe subsystem, DMA and Crypto through specialized HW units in Nitro Cards.- Debug complex, system-level, multi-component issues across multiple layers from kernel to application- Profile system performance activity and drive optimizations across our software stack- Deliver production-quality code and support its operation in the production environmentAbout the teamOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.Diverse ExperiencesAWS 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.About AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.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.BASIC QUALIFICATIONS- Experience as a mentor, tech lead or leading an engineering team- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience- 5+ years of experience with programming language: C or C++- 5+ years of experience in embedded Linux systems or NVMe Subsystem or other Storage ...

By applying to this position, your application will be considered for all locations we hire for in the United States.Are you excited about Machine Learning, chip acceleration, compilers, storage, systems or EC2? Are you passionate about delivering high quality services that affect hundreds of thousands of users? We are the dubbed the "secret sauce" behind AWS's success with development centers in the Canada and Israel, Annarpuna is at the forefront of innovation by combining cloud scale with the world’s most talented engineers.The Annapurna team hires for multiple disciplines Software and Hardware engineers including but not limited to compiler engineer, machine learning engineer, runtime engineer, performance engineer and ML chip accelerator, ASIC, physical designs, SDE in Test. Because of our teams’ breadth of talent, we’ve been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and F1 EC2 Instances, in machine learning with AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe.If this sounds exciting to you - come build the future with us!Key job responsibilitiesInnovating and delivering creative SW Designs to develop new services, solve operational problems, drive improvements in developer velocity, or positively impact operational safetyWriting requirements capturing documents, design documents, integration test plans, and deployment plansCommunicating status and progress of deliverables to schedule, and sharing learnings/ innovations with your team and stakeholdersBASIC QUALIFICATIONS- Currently enrolled in, or completed a Bachelor’s degree program or higher in Computer Science, Computer Engineering, Electrical Engineering or related field- To qualify, applicants should have earned a Bachelor’s or Master’s degree between May 2023 to September 2025. Possible start dates for this role are between January 2025 to October 2025.- Programming experience in internship or coursework with programming language such as Python and/or C or C++.Candidates with strong interests and academic qualifications/research focus in two of the following:- Distributed systems, algorithms (MPI, NCCL, or similar)- Operating System - Linux system programming/services- Computer architecture- System Development- Complexity analysis ...

Want to help drive the success of Machine Learning technologies at AWS? Do you have the skills and motivation to build automation that supports the success of peer teams? We want to talk to you! We seek a Sr. Software Development Engineer for the Machine Learning (ML) Infrastructure team to build the tools that are used to guarantee top performance of AWS ML and High Performance Computing (HPC) technologies developed by our organization. Bring your exceptional knowledge of CI/CD automation, ML and HPC benchmarks and applications to bear on the cutting-edge software we develop. Join us as we expand the AWS offerings for AI, including Trainium, Graviton and the Elastic Fabric Adapter (EFA). Key job responsibilitiesBe the lead engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use internal Amazon CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve. A day in the lifeYou use Typescript and the CDK to ensure all infrastructure setup is code (IoC), reviewed and committed to automated pipelines. You find innovative ways to schedule work using SLURM and Active Directory, supporting multiple teams of developers while keeping cluster costs down. You write excellent documents that communicate clearly to peers, stakeholders, and leadership what the team is doing and the plan for future work. You draw on your experience as a software developer to mentor other engineers. About the teamWe are part of Annapurna Labs, a subsidiary in AWS that builds software and hardware that make ML on EC2 work. Our organization is a dedicated group of innovators that have invented new networks, new silicon, new software suites, and combined those to entice customers to move immense ML and HPC workloads to the cloud. The ML Infrastructure team is laser focused on making AWS the best and most cost-effective place for customers to do AI at scale. Diverse ExperiencesAWS 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.About AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.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.BASIC QUALIFICATIONS- 5+ years of non-internship professional software development 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- 5+ years experience coding in Python, Typescript, CDK- Experience developing highly automated CI/CD pipelines (Jenkins preferred)- Proficiency working with Linux, ideally including Containers- Experience with Clustered ML or HPC Applications or Benchmarks, especially using SLURM or in AWS ...

Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. AWS has the broadest and deepest set of machine learning and AI services for our customers’ businesses.Annapurna Labs part of AWS is seeking highly experienced Hardware Test Engineers, System Test Engineers, Manufacturing Test Engineers, and System Validation Engineers to enable high quality and efficient testing for the next generation of our cloud server platforms. Our success depends on our world-class infrastructure as we are handling massive scale and rapid integration of emergent technologies. As a member of the Machine Learning Acceleration team you will be responsible for the enablement and improvement of our system level manufacturing environment.You will work on developing tests that ensure functionality and capability of our custom hardware used in the AWS server fleet. You will develop expertise in the top-to-bottom functionality of the entire system as well as the intended customer applications and stress the system from a customer perspective. You will work together with other engineering teams to develop, maintain, and improve manufacturing test code for new and existing products. You’ll work with both high-level and low-level operating system constructs to create first-boot images for products in manufacturing. You will develop and maintain the deployment and distribution system to ensure that our manufacturing partners have access to appropriate versions of our software as soon as it’s available. You will respond to new issues raised by our manufacturing partners, analyze logs and failures, and then develop and deploy solutions to those issues. You will develop documentation as well as testing and debug procedures for our manufacturing partners to follow. Key job responsibilities- Enable and maintain mass volume production testing, working with our ODMs and JDMs to verify stable high-quality execution- Drive ODM and JDM deliveries to ensure production manufacturing quality- Identify and develop tests needed to enhance coverage and increase failure granularity.- Debug test hardware and software used for system level and server level mass production- Develop manufacturing tests to exercise hw components and collect data for large scale analysisWe are open to hiring candidates to work out of one of the following locations:Austin, TX, USABASIC QUALIFICATIONS- Bachelor's degree in Electrical Engineering or Computer Engineering- 4 + years of experience developing embedded systems code and hardware interfaces (I2C, UART, SPI, JTAG, PCIe, etc.)- Experience with Python, BASH or other scripting language- Experience analyzing yield and bin pareto- Experience working with system management components (BMC, BIOS, CPLD, etc)- Experience with debugging and root cause investigations using hardware schematics and tools such as logic analyzers- Strong background working in UNIX environments ...

In Annapurna Labs we are at the forefront of hardware/software co-design not just in Amazon Web Services (AWS) but across the industry. The Machine Learning Fleet Operations Team is looking for candidates interested in diving deep into our "fleet" of Machine Learning servers deployed around the world.Do you like solving mysteries? Great! Figuring out what that light switch with no obvious function actually does? Me too! Are you wearing a smartwatch to monitor your sleep and activity over time to optimize your routines? You'll fit right in. Does the word exabyte excite you? Let's get to work.We are seeking an experienced TPM to help drive solutions in the highly technical machine learning server hardware space. Our team has end to end ownership of some of the most advanced server hardware in the world. We drive technical debug efforts and write truly massive scale autonomous software to monitor, optimize, and remediate machine learning hardware. Come join us!Key job responsibilitiesMember of a team responsible for system remediation, operational excellence, and customer experience on bleeding edge ML productsUtilize data to root cause hardware failures and identify live trends on the most complex systems in AWSImplement and improve system level testing across the product lifecycleInterface, communicate, and collaborate across organizations within AWSDive deep on issues at the intersection of hardware and softwareA day in the lifeThe MLA Fleet Operations team was formed to maintain an exceptionally high quality bar for our fleet of advanced machine learning server products. We perfect the customer experience by developing scalable software for rapid incident response times and data visualization as well as diving deep into hardware issues as they arise.About the teamOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.BASIC QUALIFICATIONS- 5+ years of technical product or program management experience- 7+ years of working directly with engineering teams experience- 3+ years of software development experience- 5+ years of technical program management working directly with software engineering teams experience- Experience managing programs across cross functional teams, building processes and coordinating release schedules ...

Utility Computing (UC)AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.About AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Diverse ExperiencesAWS 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 BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.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. Custom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data centers including AWS Inferentia, our custom designed machine learning inference datacenter server. Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. We’re looking for an ASIC Design Eengineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.Key job responsibilities- integrate multiple subsystems into top level SOC, ensure correct clock/reset/functional/DFT signal routing- As a key member of the ASIC design team, you will implement and deliver high performance, area and power efficient RTL to achieve design targets and specifications.- Analyze design, microarchitecture or architecture to make trade-offs based on features, power, performance or area requirements.- Develop micro-architecture, implement SystemVerilog RTL, and deliver synthesis/timing clean design with constraints.- Perform lint and clock domain crossing quality checks on the design.- Work with with architects, other designers, verification teams, pre- and post-silicon validation teams, synthesis, timing and back-end teams to accomplish your tasks.You will thrive in this role if you:- Are familiar with scripting in Python- Are proficient with assertions- Have good debug skills to analyze RTL test failures- Have a "Learn and Be Curious" mindsetAbout the teamCustom SoCs (System on Chip) live at the heart of AWS Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data centers including AWS Inferentia, our custom designed machine learning inference datacenter server. Our success depends on our world-class server infrastructure; we’re handling massive scale and rapid integration of emergent technologies. We’re looking for an ASIC Design Eengineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.BASIC QUALIFICATIONS - B.S. in Electrical Engineering or related technical field - 5+ years of experience in RTL design for SOC - 5+ years of experience VLSI engineering - 5+ years of experience with code quality tools including: Spyglass, LINT, or CDC ...

Annapurna Labs builds high-performance hardware and software solutions used in AWS data centers globally. We’re looking for a software development manager with a focus on runtime development of Neuron SDK. As a Software Development Manager for the Neuron Runtime team you will be responsible for leading a strong and excellent team of engineers in design, development, test, and deployment of this Neuron runtime software, including drivers, tools and testing of future and past ML platforms (Pre/Post Silicone). A successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, excellent project skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You will be helping to hire and build your team and systems.Key job responsibilities- Responsible for the over-all systems development life cycle for our existing and future ML platforms.- Management and execution against project plans and delivery commitments - Manage the day-to-day activities of the engineering team within an Agile/Scrum environment - Management of departmental resources, staffing, mentoring, enhancement, and maintaining a best-of-class engineering team - Report on status of development, quality, operations, and system performance to management- Work closely with across different teams such as HW Design, HW verification, ML Software teams and make decisions to bring the next ML platforms to AWS.About the team*Utility Computing (UC)* AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.**Why AWS**Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.**Diverse Experiences**Amazon 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.**Work/Life Balance* *We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. **Inclusive Team Culture* *Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.**Mentorship and 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. BASIC QUALIFICATIONS- 3+ years of engineering team management experience- 7+ years of working directly within engineering teams experience- 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations- Experience partnering with product or program management teams ...