Sr. GenAI & ML Specialist Solutions Architect, ASPI Auto & Manufacturing

Are you a customer-obsessed builder passionate about helping customers achieve their full potential? Do you have the business acumen and technical pre-sales expertise to help customers evaluate, design, and adopt AWS as their strategic platform for Generative AI and ML workloads? Do you enjoy building impactful AI solutions? Join the Worldwide Specialist Organization (WWSO) within the Data & AI Specialists team for Automotive & Manufacturing as a Senior Generative AI & ML Specialist Solutions Architect—a senior individual contributor role requiring deep technical expertise and executive-level customer engagement.
The Worldwide Specialist Organization (WWSO) is part of the AWS Specialists and Partners organization, responsible for driving revenue and accelerating adoption of cloud and partner services across private and public sector customers. We work backwards from our customers’ most complex and business-critical challenges to develop and execute go-to-market plans that transform ideas into scalable, high-impact businesses. WWSO teams include business development specialists and technical solution architects. As part of WWSO, you will contribute across the full lifecycle of AWS customer initiatives—from shaping new service and solution concepts to accelerating adoption of established offerings. We pride ourselves on thinking big, delivering exceptional customer outcomes, and collaborating seamlessly across AWS as #OneTeam.


Key job responsibilities
In this role, you will translate customer business challenges into solutions leveraging AWS. You will define, design, and deploy targeted architectures that accelerate adoption of AWS Generative AI and ML services. You will engage with senior engineers, architects, product leaders, data scientists, and executives at strategic enterprise customers to influence architectural decisions and provide structured feedback to AWS product teams.
AWS collaborates with a range of partners in the AI ecosystem—including leading third-party foundation model providers (e.g., Anthropic, Meta, Mistral, etc.). You will execute joint go-to-market motions with these partners and build proof-of-concepts for AI- and agent-enabled applications.
As the ideal candidate, you bring a deep technical background and the business acumen required to lead complex engagements with large enterprises. You have hands-on expertise in traditional ML concepts as well as emerging areas such as LLMs, RAG, fine-tuning, AI system evaluation, prompt engineering, agents, and AIOps. You are able to credibly advise senior technical and executive stakeholders on architectural trade-offs, risks, and long-term strategy.

Core Responsibilities:
- Collaborate with business development colleagues to provide technical input into go-to-market strategy and support field marketing through technical events, campaigns, and customer engagements

- Lead complex technical problem solving to unblock customers’ most critical workloads

- Represent the voice of the customer and collaborate with field and central teams to bring customer feedback to product teams

- Act as a thought leader in Generative AI by sharing best practices through AWS blogs, whitepapers, reference architectures, code samples, and public speaking engagements such as AWS Summits and AWS re:Invent

- Guide and support an internal AWS community of technical subject matter experts aligned to your customers, including the creation of field enablement materials for the broader Solution Architect population


About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.

Basic Qualifications

- Bachelor’s degree (Master’s or PhD preferred) in Computer Science, Engineering, Mathematics, Applied Statistics, Data Science, or related fields
- Strong conceptual understanding of machine learning fundamentals and modern Generative AI techniques
- Deep expertise in software engineering, cloud architecture, data analytics, and AI/ML systems
- Proven track record in conceptual development, solution design, and implementation of enterprise applications using data, ML, and AI
- Experience in customer-facing roles such as pre-sales, consulting, or similar
- Fluent English (written and spoken) required

Preferred Qualifications

- Experience in adjacent technology domains such as database systems, big data, and analytics
- AWS certifications strongly preferred (e.g., Solutions Architect, Machine Learning Engineer, Data Engineer)
- Experience working with large enterprises in the Automotive and Manufacturing industries
- Strong preference for experience in technical pre-sales or customer-facing architecture roles
- German language skills

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