Partner Solutions Architect, Cx & Business Applications, Aws Partner Field Emea

Amazon Amazon · Big Tech · M, Spain +1 · Solutions Architect

This role involves working with AWS partners to enable them to build and bring to market solutions using AI-driven development methodologies and tools, focusing on customer experience and workforce productivity. The Partner Solutions Architect will provide technical guidance, develop enablement content, and support go-to-market motions, including building prototypes and proof-of-concept solutions that demonstrate AI-DLC in practice. The role emphasizes thought leadership on Next-Generation Software Development and representing partner needs to AWS service teams.

What you'd actually do

  1. Support Partner go-to-market motions by providing technical guidance and support, thought leadership on AI-assisted development, code modernization, and developer productivity
  2. Enable AWS Partners and internal AWS teams on the adoption and usage of AI-Driven Development Lifecycle (AI-DLC) methodologies and AI-native IDEs, covering positioning, workshop delivery, and customer engagement across the full lifecycle
  3. Create best practices and architectural guidance on Next-Generation Software Development, being a thought leader on the area.
  4. Be the technical reference on Next-Gen Development for the EMEA Partner Organization, collecting and exposing all the work done across EMEA.
  5. Collaborate with AWS account teams, professional services, and commercial sales to bridge partner capabilities with customer demand for NextGen Development

Skills

Required

  • Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
  • Experience in a technical role within a sales organization
  • Knowledge of software development tools and methodologies
  • Technical degree (Computer Science, Software Engineering, or equivalent) and/or relevant industry experience
  • Experience in software development, application architecture, or DevOps engineering
  • Working knowledge of modern software development practices: CI/CD, infrastructure as code, automated testing, containerization
  • Familiarity with at least one modern programming language (Python, Java, TypeScript, Go, .NET)
  • Experience designing and delivering technical workshops or enablement sessions to engineering audiences
  • Experience working in a partner-facing or channel-facing technical role
  • Fluent written and verbal communication skills in English and another European language

Nice to have

  • Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
  • Experience with AI-assisted development tools and methodologies (agentic coding, spec-driven development, AI pair programming)
  • Hands-on experience with application modernization: migrating legacy codebases, refactoring monoliths to microservices, or language/framework upgrades
  • Knowledge of generative AI foundations: large language models, prompt engineering, context engineering, retrieval augmented generation (RAG)
  • Experience enabling or developing partner ecosystems (system integrators, ISVs, consulting firms)
  • Familiarity with IDE extensibility, developer tooling, and software supply chain practices
  • Experience with cloud-native application development on AWS (Lambda, ECS/EKS, Step Functions, CDK)
  • AWS certification (e.g. AWS Solutions Architect Associate or Professional, Developer Associate)
  • Experience with public speaking, technical blogging, or producing educational content
  • Fluent written and verbal communication skills in an additional European language

What the JD emphasized

  • AI-assisted development
  • AI-Driven Development Lifecycle (AI-DLC)
  • AI-native IDEs
  • Next-Generation Software Development
  • AI-DLC methodology in practice
  • AI handles routine development tasks
  • AI-DLC workshop
  • code generation
  • Kiro's spec-driven development
  • AI-powered development

Other signals

  • AI-assisted development
  • AI-Driven Development Lifecycle (AI-DLC)
  • AI-native IDEs
  • Next-Generation Software Development
  • AI-DLC methodology in practice
  • AI handles routine development tasks
  • AI-DLC workshop
  • code generation
  • Kiro's spec-driven development
  • AI-powered development