Senior Security Data Scientist, Global Services Security

DESCRIPTION

This role with partner with the existing Security Experts to validate that security controls are enabled throughout the lifecycle of traditional Machine Learning and Generative AI phases of model development. The security controls will be defined from the early experimentation phases to model fine-tuning to model deployment and ongoing operational governance.

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Key job responsibilities

• Lead the development of security guidance on the use of AI/ML, particularly generative AI

• Collaborate with security experts to validate and recommend security controls applicable for all phases of AI/ML/Gen AI development lifecycle

• Design, build, test, and help deploy ML and generative AI solutions that have measurable business and customer impact in security.

• Interact with internal and external customers to understand their business problems and help them in implementation of their generative AI and ML solutions

• Facilitate discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation

• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder

• Create detailed security documentation of solutions using reference architectures and implementation/configuration guidance

• Collaborate with AI/ML peers to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges

• Provide customer and market feedback to Service and Engineering teams to help define product direction

• Work with a cross section of AI experts to develop solutions that will be piloted with customers for their production workloads

About the team

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.

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.

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.

Hybrid Work

We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-

person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or

in a flexible, hybrid work model near one of our Amazon offices.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Dallas, TX, USA | Herndon, VA, USA | Irvine, CA, USA | New York City, NY, USA | Seattle, WA, USA

BASIC QUALIFICATIONS

• Bachelor's degree in computer science, engineering, mathematics or equivalent

• Experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar

• 5+ years of relevant experience in developing and evaluating deep learning models and/or systems, including batch and real-time data processing

• Experience with two or more of prompt engineering, retrieval-augmented generation (RAG), vector databases, or LLM frameworks such as Hugging Face, Langchain or LlamaIndex.

• 3+ years of experience in security architecture or engineering including application security, secure SDLC, or cloud security

PREFERRED QUALIFICATIONS

• Graduate degree (MS or PhD) in computer science, data science, or related technical, math, or scientific field

• Experience in building Generative AI applications and large foundation models preferably using AWS services such as Sagemaker, Bedrock, Amazon Q, Kendra, OpenSearch, and Neptune

• Scientific thinking and the ability to invent; a track record of thought leadership and contributions that have impacted products and customers

• Familiarity and implementation experience with enterprise security solutions such as web application firewalls, IDS/IPS, SIEM, DLP, DDOS mitigation

• Understanding architectural implications of meeting industry standards such as PCI DSS, ISO 27001, HIPAA, NIST AI RMF, OWASP Top 10 for LLM, ISO/IEC 42001, and NIST/DoD frameworks

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.