Principal Solutions Architect - GenAI/ML, AGS-WWSO EMEA

Amazon; Torino; In loco; EUR 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

A global cloud service provider seeks a Principal Solutions Architect to guide clients in adopting Generative AI solutions on AWS. The ideal candidate will have extensive experience in cloud computing, proficient communication skills in Hebrew and English, and a strong technical background in machine learning. The role involves providing architectural guidance, leading design discussions, and educating clients on AWS benefits, contributing to both customer success and revenue growth.

Servizi

Work-life balance

Mentorship and career growth

Inclusive culture

Competenze

• 15+ years of experience in software development, cloud computing or related fields.
• Experience in deploying GenAI models on cloud infrastructure.
• Fluent in Hebrew and English.

Mansioni

• Provide architectural guidance to promote AWS adoption.
• Lead discussions to design solutions on AWS.
• Educate customers on AWS value.

Conoscenze

Communication skills

Machine learning fundamentals

Cloud computing

MLOps tools

Strumenti

Pytorch

TensorFlow

Amazon SageMaker

Descrizione del lavoro

Principal Solutions Architect - GenAI/ML, AGS-WWSO EMEA

Job ID: 3144672 | AWS EMEA SARL (Israel Branch)

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and unwavering support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer‑first approach is how we built the world's most adopted cloud. Join us and help us grow.

The candidate will be responsible for advising on Generative AI and core services for the largest customers in EMEA.

Key job responsibilities

• Act as a strategic technical leader in the field to provide architectural guidance and recommendations necessary to promote & accelerate customer adoption of AWS.
• Ensure customer & partner success in designing, building and migrating applications, software, and services on the AWS platform.
• Lead architectural discussions and design exercises to create world‑class solutions built on AWS while ensuring solutions are designed for successful deployment in the cloud.
• Be an AWS evangelist; educate customers & partners of all sizes on the value proposition of AWS.
• Build deep relationships with senior technical individuals within customers & partners to enable them to be cloud advocates.
• Capture and share best‑practice knowledge amongst the AWS solutions architect community.
• Author or otherwise contribute to AWS customer‑facing publications such as white papers, blogs, and proof of concepts.
• In partnership with the sales & partner team, formulate, and execute a sales strategy to exceed revenue objectives through the adoption of AWS & its partner solutions.
• Conduct one‑to‑few and one‑to‑many training sessions to transfer knowledge to customers considering or already using AWS.
• Act as a technical liaison between customers, service engineering teams and support.

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.

Inclusive Team Culture

AWS values curiosity and connection. Our employee‑led and company‑sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

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.

Basic Qualifications

• 15+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• Experience with building, validating and deploying GenAI models and applications on cloud infrastructure.
• Sound knowledge of machine learning fundamentals, with working knowledge of frameworks such as Pytorch, TensorFlow, JAX or MXNet.
• Knowledge of MLOps tools and workflows for model development, validation, and deployment.
• High level of communicating effectively across internal and external organizations, with both technical and non‑technical audiences.
• Fluent written and verbal communications skills in Hebrew and English with demonstrated ability to communicate technical choices to business and technology stakeholders.

Preferred Qualifications

• Professional experience architecting/operating solutions built on AWS and/or AWS certification (e.g. AWS Solutions Architect Associate or Professional)
• Hands‑on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high‑speed networking.
• Understanding of technical details and techniques used in tuning generative AI foundation models using techniques like RAG, PEFT, RLHF, DPO
• Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker
• Experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real‑time data processing

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.