Sr. Deep Learning Architect , Global Services Security

at  Amazon Web Services Inc

• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• Experience coding in Python, R, Matlab, Java or other modern programming language
• 3+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
• 4+ years of experience hosting and deploying ML or GenAI solutions with at least 2 of the following capabilities: training, fine-tuning, prompt engineering, retrieval-augmented generation (RAG), vector databases, or LLM frameworks such as Hugging Face, Langchain or LlamaIndex
• Experience working directly with customers to translate business opportunities with ML or GenAI solutions
  Are you looking to work at the forefront of AI/ML/Generative AI? Would you be excited to
  apply cutting edge security to protect and scale AI/ML/Generative AI workloads? The Global
  Services Security Solutions Team provides pioneering security solutions to enable customers
  achieve their business outcomes. This role with partner with security experts to implement
  security controls enabled throughout the lifecycle of ML and Generative AI phases of
  development. The security controls will be defined for all phases including governance,
  experimentation, testing, deployment and ongoing operational excellence. You will work
  directly with customers and innovate in a fast-paced organization to empower customers to
  apply both security and speed to market for their AI/ML/Generative AI workloads.
  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 for AI/ML/Generative AI workloads built using

Amazon SageMaker, Amazon Bedrock, and Amazon Q

• 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

• 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 stakeholders

• Create detailed security documentation of solutions using reference architectures and

implementation/configuration guidance

• 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, NY, USA | Seattle, WA, USA

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• Experience in building ML or Gen AI applications and large foundation models preferably using AWS services such as Sagemaker, Bedrock, Amazon Q, Kendra, OpenSearch, EMR, S3, Step Functions, Lambda, EC2, and Neptune
• Strong working knowledge of deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training, machine learning, and statistics
• Knowledge of security architecture that includes application security, secure SDLC, or cloud security
• 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 $138,200/year in our lowest geographic market up to $239,000/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

• Lead the development of security guidance for AI/ML/Generative AI workloads built usin