Solutions Architect, AI Transformation, Enterprise, Enterprise Solutions Architecture, Switzerland

AWS EMEA SARL (Switzerland Branch); Genf; On-site; CHF 130,000 - 180,000; Full time

Job summary

AWS EMEA SARL (Switzerland Branch) in Geneva is seeking a Solutions Architect to be the trusted technical advisor to enterprise customers, guiding them from initial conversations through to production as they adopt AI and generative AI across the development lifecycle.

You will partner with AI teams, design architectures with model selection, data pipelines, risk and cost considerations, and help customers translate AI potential into measurable business outcomes while representing AWS at

Qualifications

• Experience building with AI/ML, including generative AI (foundation models, retrieval-augmented generation, or agentic patterns)
• Experience applying AI/ML to software development and/or business transformation use cases
• Experience designing, implementing, or consulting on applications and/or infrastructure
• Experience in a customer-facing or client-facing technical role

Responsibilities

• Act as the trusted technical advisor for your customers across their adoption of AWS, from early strategy conversations through architecture, build and production.
• Lead technical deep-dives, architecture reviews, workshops and proof-of-concept engagements that move customers from AI ambition to a design they can deploy.
• Design AI/ML and generative-AI architectures: model selection, retrieval and data pipelines, agentic patterns, evaluation, cost and latency trade-offs, and the security and data-residency requirements customers bring to every conversation.
• Apply and promote AIDLC practices, helping customers change how they build using AI across the development lifecycle, and connect that to measurable business outcomes.
• Help customers build evaluation frameworks that measure models against their own success criteria, so production-readiness decisions rest on evidence.
• Own the technical narrative across audiences, from implementation detail with engineering teams to business-value framing with CTOs, Chief Data Officers and executive sponsors.
• Share knowledge with the wider Solutions Architecture and Account Management community, raising the team's collective depth in AI.
• Capture patterns and friction from customer engagements and feed them back to AWS service teams as concrete product input.
• Produce reference architectures and technical content, and represent AWS at customer briefings and industry events.

Skills

AI/ML expertise

Generative AI

Architectural design

Customer-facing

Job description

As a Solutions Architect, you are the trusted technical advisor to your customers, partnering with them across their journey on AWS. You work with enterprise customers to understand their goals, design the architectures that get them there, and guide them from first conversation through to production. You are comfortable moving between the whiteboard with a customer's architects and the boardroom with their executive sponsors, and you earn trust by being genuinely useful at both.

This role carries that generalist Solutions Architect mandate with a focus on AI transformation. It spans both sides of that work: helping customers transform how they build, applying AI across the development lifecycle (AIDLC), and helping them transform their business with AI. You help customers understand what is genuinely possible, separate what is ready from what is not, and build the architectures and the confidence to put AI into production.

You work closely with the AI teams, and you help customers connect AI capability to real business outcomes rather than experiments.

Key job responsibilities

• Act as the trusted technical advisor for your customers across their adoption of AWS, from early strategy conversations through architecture, build and production.
• Lead technical deep-dives, architecture reviews, workshops and proof-of-concept engagements that move customers from AI ambition to a design they can deploy.
• Design AI/ML and generative-AI architectures: model selection, retrieval and data pipelines, agentic patterns, evaluation, cost and latency trade-offs, and the security and data-residency requirements customers bring to every conversation.
• Apply and promote AIDLC practices, helping customers change how they build using AI across the development lifecycle, and connect that to measurable business outcomes.
• Help customers build evaluation frameworks that measure models against their own success criteria, so production-readiness decisions rest on evidence.
• Own the technical narrative across audiences, from implementation detail with engineering teams to business-value framing with CTOs, Chief Data Officers and executive sponsors.
• Share knowledge with the wider Solutions Architecture and Account Management community, raising the team's collective depth in AI.
• Capture patterns and friction from customer engagements and feed them back to AWS service teams as concrete product input.
• Produce reference architectures and technical content, and represent AWS at customer briefings and industry events.

A day in the life

Your morning might start with a working session with a Swiss enterprise customer's leadership, mapping where generative AI can change how their teams build software and run operations.

Next, you join their engineers to design an agentic solution on Amazon Bedrock AgentCore and talk through security, cost and scale.

After lunch, you run a hands-on AI-DLC workshop with the account team, then build a proof of concept that turns a promising idea into a measurable pilot.

You end the day sharing what you learned with the wider SA community and passing customer feedback to AWS service teams.

BASIC QUALIFICATIONS

• Experience building with AI/ML, including generative AI (foundation models, retrieval-augmented generation, or agentic patterns)
• Experience applying AI/ML to software development and/or business transformation use cases
• Experience designing, implementing, or consulting on applications and/or infrastructure
• Experience in a customer-facing or client-facing technical role

PREFERRED QUALIFICATIONS

• Experience delivering AI/ML and generative-AI workloads in production on any cloud or platform
• Knowledge of enterprise customer segments and how large organizations adopt new technology
• Experience in a specific technology domain (e.g. software development, systems engineering, infrastructure, security, networking, data & analytics)
• Professional working proficiency in French (local language in Geneva) or German alongside English