Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Are you a customer-obsessed builder passionate about helping customers build faster, smarter, and more reliably with AI? Join Amazon's Worldwide Specialist Organization (WWSO) Startup team as a GTM Specialist Solutions Architect for Agentic Engineering. In this role, you will engage with startup customers, from CXO/VP engineering to developers, to drive adoption of AWS Agentic Engineering offerings including Kiro, Claude Code on Bedrock, Codex on Bedrock, and AWS Frontier Agents. You will become a trusted advisor, providing technical thought leadership in AI-powered software development workflows and embedding AI capabilities throughout the software development lifecycle (SDLC). You will design and execute go-to-market programs targeting the developer community, including meet-ups, hackathons, university seeding, and ISV partnerships to drive organic product-led adoption. Collaborating closely with AWS service and engineering teams, you will surface customer feedback, influence roadmap priorities, and co-create solutions that solve real startup challenges. Additionally, you will guide and support AWS internal technical subject matter experts by creating enablement materials, demo assets, open-source samples, and workshop content to help position Kiro and Agentic Engineering capabilities within customer architectures.

A Day in the Life
The WWSO Startup team helps startups scale quickly and cost-effectively on AWS by recommending the right technologies and accelerating adoption. As a Specialist Solutions Architect focused on Agentic Engineering, you will be a storyteller and technologist, articulating the value of AI-powered development through demos, reference architectures, and real customer outcomes. You will work with promising startups, engage lighthouse customers building with agentic tools at scale, scale technical knowledge via products and programs, and gather critical startup feedback to inform product roadmaps. This role offers the opportunity to work at the forefront of AI and software engineering innovation, helping startups succeed with AWS technologies.

Experience
- 7+ years design, implementation, or consulting experience with distributed applications or developer tooling
- 5+ years technical experience in at least one of the following: AI/ML, LLMs, generative AI, or modern SDLC automation (CI/CD, DevSecOps, infrastructure-as-code)
- Experience in a customer-facing role engaging with executives, technologists, or partners to solve business problems with advanced technologies
- Startup background and experience at a VC or PE-backed firm in a Technical Executive capacity

About You
- Passionate about AI-powered software development and startup ecosystems
- Strong data-based storytelling skills with comfort speaking to startup executives and developer communities
- Ability to adapt quickly to new technologies in a fast-moving competitive landscape
- Collaborative mindset with experience working across teams and partners to scale adoption
- Enthusiastic about building communities and delivering technical enablement content

Qualifications
- Bachelor's degree or above in computer science, computer engineering, or related field required
- Preferred: Master's degree or above in engineering, management, technology, computer science, engineering, or mathematics
- Preferred: Cloud Technology Certification such as Solutions Architecture, Cloud Security Professional, or Cloud DevOps Engineering
- Familiarity with open-source software and software development tools common to startups
- Hands-on experience with AI coding assistants and agentic developer tools (e.g., Kiro, Cursor, Claude Code, GitHub Copilot, Codex, Windsurf)
- Experience designing or implementing CI/CD pipelines, DevSecOps workflows, or SDLC automation at scale
- Familiarity with Agentic AI architectures including multi-agent orchestration, tool-use patterns, MCP (Model Context Protocol), and autonomous agent frameworks
- Proficiency with design, deployment, and evaluation of LLM-powered agents and orchestration tools (e.g., Strands Agents SDK, LangGraph, CrewAI)