- 10+ years' professional experience in software development in languages like Python, Java, or Scala
- 10+ years' experience working with RESTful API and general service-oriented architectures
- 5+ years of experience in technical sales and architecture design with focus on AI services for computer vision, language / speech, bots, anomaly detection, text search, forecasting, or personalization.
- 5+ years of experience with streaming & batch services, API development, NoSQL databases, and Serverless technologies.
- 5+ years of experience with DevOps tools to build CI/CD pipelines and automation of cloud services deployment.
- 5+ years of design/implementation/consulting experience building public cloud solutions
Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on Amazon Web Service (AWS)? Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists and 3) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, Amazon Forecast, Amazon Personalize, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.
AWS is looking for an AI Services Solutions Architect (Artificial Intelligence SA), who will be the Subject Matter Expert (SME) for helping customers in the AMERICAS design solutions that leverage our AI services. You will partner with Solution Architects, Sales, Business Development and the AI Service teams to enable customer adoption and revenue attainment for Amazon Transcribe, Amazon Rekognition, Amazon Comprehend, Amazon Forecast, Amazon Personalize, and the other AWS AI services in the AMERICAS. You will develop white papers, blogs, reference implementations, labs, and presentations to evangelize AWS AI design patterns and best practices for all of the AWS AI services. And, most important - you will act as the steward for developing winning AI capabilities for our customers.
If you are a qualified and accepted candidate, you may work out of any of the following cities: Southern California (i.e. south of San Diego to north of Los Angeles), Bay Area California, or Seattle.
Travel up to 50% across the AMERICAs may be possible.
Roles and Responsibilities
- Thought Leadership – Evangelize AWS AI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc.
- Partner with SAs, Sales, Business Development and the AI Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Translate, Amazon Polly, Amazon Forecast, Amazon Personalize, and the other AI services.
- Act as a technical liaison between customers and the AI services engineering teams to provide customer driven product improvement feedback.
- Develop and support an AWS internal community of AI related subject matter experts in the AMERICAS.
Inclusive Team Culture
Here 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our 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 Growth
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 based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
- Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking to large audiences.
- Experience with AWS SageMaker or other Data Science platforms
- Professional experience architecting/operating solutions built on AWS
- Experience with ingesting and processing structured and unstructured data at scale.
- Experience deploying production-grade solutions on public cloud platforms
- Experience with AWS AI services including Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Translate, Amazon Polly, Amazon Forecast, and Amazon Personalize.
- Experience with AWS services related to the AI/ML ecosystem, particularly AWS Kinesis, AWS Lambda, Machine Learning, SageMaker, IoT, Amazon DynamoDB, Elastic Search, Amazon S3, AWS Container Services like EKS, Fargate etc.
- Experience communicating effectively across internal and external organizations, for complex mission-critical solutions
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit US Disability Accommodations.