Principal Tech BDM, AI/ML, Private Equity

Job summary
Are you energized to create new markets for Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technology? Do you love building new businesses? AWS is seeking an ML specialist to define, build and lead the business development efforts at AWS to commercialize the AWS ML platform for AWS’ Private Equity customers.

You will be a leading voice of AWS ML. You will leverage worldwide programs or campaigns and work closely with AWS business development, product management, sales, marketing, solutions architect, and partner teams to position the AWS ML platform for customers and partners, to provide guidance on the value proposition and to communicate the benefits customers can achieve with our ML services. You will define the go to market (GTM) strategy for the AWS ML platform to accelerate adoption of AWS ML by Private Equity funds and their portfolio companies.

You will synthesize data and information gathered from these customer and partner engagements into the AWS GTM strategy for ML to successfully commercialize the platform. This entails deriving succinct findings, developing strategic insights, and persuasively communicating those findings and perspectives from customer engagements to product and sales teams, including senior management.

The ideal candidate will possess deep practical expertise in the application of ML to accelerate business objectives. This will include a demonstrated track record of driving ML adoption across a broad range of customers, and an ability to draw on global best practices to enable ML adoption within the Private Equity industry.

The ideal candidate will also have the technical depth and business experience to easily communicate the benefits of ML services, platforms and frameworks in the AWS cloud to a range of customer personas within PE funds and their portfolio companies.

Finally, the ideal candidate will have a background that enables them to create scalable programs that leverage their expertise to enable an even broader range of customers to benefit from ML on AWS.


About Us
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve 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.

Work/Life Balance
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.

This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.

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.

Basic Qualifications

· 10+ years’ experience in enterprise sales, business development, management consulting, or in roles leading large and complex technology initiatives
· 5+ years’ experience applying ML for diverse businesses and designing ML solutions to accelerate business goals
· 5+ years' experience driving implementation of technology solutions
· BA/BS degree or equivalent experience required

Preferred Qualifications

· Deep experience in the Private Equity industry, including a demonstrated track record of successfully accelerating the adoption of AI/ML by Private Equity funds and their portfolio companies
· Recognized thought-leader in the ML industry, demonstrated by public presentations, delivering webinars, and regularly contributing to industry publications on topics such as the business applications of ML
· Technical proficiency in each of the core components of a machine learning workflow (i.e. data preparation, model training, deployment, MLOps), including the ability to code in python, R or other widely used data science language
· Holder of AWS ML certification or other specialty certifications
· Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)




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, please visit https://www.amazon.jobs/en/disability/us.