DESCRIPTION

Are you passionate about Generative AI (GenAI)? This is an exciting opportunity to shape the future of AI and make a real impact on our customers’ generative AI journeys. Join our team and play a pivotal role in shaping the future of Responsible Generative AI at AWS while prioritizing security, privacy, and ethical AI practices. In this role, you will play a pivotal role in guiding AWS customers on the responsible and secure adoption of Generative AI, with a focus on Amazon Bedrock, our fully managed service for building generative AI applications.

The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which 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. We work backwards from our customer’s most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you’ll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam

AWS is looking for a Generative AI Data Scientist, who will guide customers on operationalizing Generative AI workloads from Proof-of-Concept to Production, with appropriate guardrails and responsible AI best practices, including techniques for mitigating bias, ensuring fairness, vulnerability assessments, red teaming, model evaluations, hallucinations, grounding model responses, and maintaining transparency in generative AI models. You’ll develop technical assets demonstrating guardrails for content filtering, redacting sensitive data, blocking inappropriate topics, and implementing customer-specific AI safety policies. The technical assets you develop, will equip AWS teams, partners, and customers to responsibly operationalize generative AI, from PoCs to production workloads. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.

As part of the Generative AI Worldwide Specialist organization, you will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review.

You must have deep understanding of Generative AI models, including their strengths, limitations, and potential risks. You should have expertise in Responsible AI practices, such as bias mitigation, fairness evaluation, and ethical AI principles. In addition you should have hands on experience with AI security best practices, including vulnerability assessments, red teaming, and fine grained data access controls.

Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation.

Travel up to 40% may be possible.

Key job responsibilities
– Guide customers on Responsible AI and Generative AI Security: Act as a trusted advisor to our customers, helping them navigate the complex world of Generative AI and ensure they are using it responsibly and securely.
– Operationalize generative AI workloads: Support customers in taking their generative AI projects from proof-of-concept to production, implementing appropriate guardrails and best practices.
– Demonstrate Generative AI Risks and Mitigations: Develop technical assets and content to educate customers on the risks of generative AI, including bias, offensive content, cyber threats, prompt hacking, and hallucinations.
– Collaborate with GenAI Product/Engineering and Customer-Facing Builder Teams: Work closely with the Amazon Bedrock product and engineering teams and customer-facing builders (Solution Architects and Technical Field Community members) to launch new services, support beta customers, and develop technical assets.
– Thought Leadership and External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS re:Invent.
– Develop technical content, workshops, and thought leadership to enable the broader technical community, including Solution Architects, Data Scientists, and Technical Field Community members.

About the team
About AWS

Diverse Experiences
AWS 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.

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 & 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.

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.

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 US Amazon offices.

BASIC QUALIFICATIONS

– 5+ years of Data Scientist or Machine Learning Solutions Architect experience preferably with a focus on AI/ML ethics and security .
– 5+ years of experience with Python to analyze datasets, train , evaluate, deploy, and optimize models.
– – 3 years Expertise in Responsible AI practices, such as bias mitigation, fairness evaluation, and ethical AI principles.
– – 3 years experience with AI security best practices, including vulnerability assessments, red teaming, and data access controls.
– 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
– 1+ year experience working with technologies related to large language models including LLM architectures, Responsible generative AI, model evaluation, and model customization techniques.
– Proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches.
– Proficient with prompt engineering, embedding model fine tuning and retrieval method evaluation and optimization approaches.

PREFERRED QUALIFICATIONS

– Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex, and Whylabs etc.
– Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM.
– Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches
– Customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, best practices, and risk mitigation.
– Master’s degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
– Should be able to interact with Chief Data Science Officers, as well as the people within their organizations.
– Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment.
– Track record of thought leadership and innovation around Machine Learning.
– Familiarity with AWS services and the cloud computing landscape is preferred.

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/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.

USA, WA, Seattle