refurbed
marketplace
InternalAIProductEngineer(f/m/x)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Internal AI Product Engineer (f/m/x) at refurbed. Skills: AI Product Engineering, AI/LLM-powered systems, Back-end engineering & architecture, Product management & discovery, Cross-functional enablement & technical leadership. Design and build back-end services, APIs, and integrations with external tools, services, and models that power internal AI tools and systems. Lead the architecture and design of internal AI tools and systems that support company-wide productivity and automation goals”
What You'll Achieve.
enable refurbed to operate as an AI-native company; support company-wide productivity and automation goals; Ship company-wide shared AI services and a baseline AI toolkit every new joiner gets on day one; embed AI into internal workflows
Industry & Context.
translate messy, cross-functional problems into clear requirements; evaluate trade-offs; unblock cross-functional delivery
workation per year, remote-first, full autonomy over their location, Candidates based in Europe (including UK) only with a valid right to work, work from our beautiful office in the vibrant heart of Vienna, office weeks, happening three times a year
What They're Looking For.
Must Have
comfortable designing for scale, reliability, and cost on GCP, Experience building AI/LLM-powered systems in production, product instincts in the classic PM sense, Stakeholder management across senior leaders and department, Deep, practical fluency with modern AI tooling and active engagement with the fast-moving ecosystem, worked extensively with multiple coding assistants (e. g. Claude Code, Codex, Cursor), knows how to structure, build, and install skills/plugins/marketplaces, can design and integrate MCPs, works fluently with subagents and agent, able to make informed build vs. buy trade-offs, Candidates based in Europe (including UK) only with a valid right to work
Nice to Have
AI comfortable designing for scale, reliability, and cost on GCP, Experience building AI/LLM-powered systems in production - from prototyping with model APIs through deployment, observability, and iteration, product instincts in the classic PM sense - has owned a product area end-to-end with discovery, PRDs, roadmap, success metrics, and measurable not just "used AI tools as a backend engineer", Comfortable balancing IC engineering work with technical leadership: setting direction, reviewing designs, and mentoring others without losing hands-on fluency, Deep, practical fluency with modern AI tooling and active engagement with the fast-moving ecosystem - has worked extensively with multiple coding assistants (e. g. Claude Code, Codex, Cursor), knows how to structure, build, and install skills/plugins/marketplaces, can design and integrate MCPs, and works fluently with subagents and agent, able to make informed build vs. buy trade-offs
What You'll Do.
Design and build back-end services
and integrations with external tools
and models that power internal AI tools and systems
Lead the architecture and design of internal AI tools and systems that support company-wide productivity and automation goals
Define technical approaches
evaluate trade-offs (build vs. buy
integration patterns)
and create implementation roadmaps
Implement and refine tooling standards
and best practices for AI development within the governance framework
Run deep-dive discovery on prioritised use cases from the AI portfolio
and surface bottom-up opportunities to feed into it
Own the product roadmap for internal AI tools - translating messy
cross-functional problems into clear requirements
Ship company-wide shared AI services and a baseline AI toolkit
Partner with the Head of Internal Technology & AI on strategy execution
technical feasibility assessments
Drive cross-functional technology initiatives to embed AI into internal workflows
Provide technical leadership and guidance to teams working on AI-related projects
Support adoption of the internal AI tools you build
through demos and hands-on integration guidance
Stay current on AI/ML trends and tooling to inform strategic decisions and identify new opportunities
How You'll Work.
Team & Collaboration
Stakeholder management across senior leaders and department; align people around trade-offs; unblock cross-functional delivery; partnering with stakeholders across the business; collaboration across departments
Communication Scope
Stakeholder management; align people around trade-offs; unblock cross-functional delivery; demos; hands-on integration guidance
Process & Methodology
roadmap, PRDs, milestones, prioritisation
Full Job Description
Founded in 2017, refurbed is Europe’s fastest-growing marketplace for refurbished products, active in 12 European countries and having surpassed €2Bn in GMV — all while being profitable. With beautiful headquarters in Vienna, we operate as a remote-first company, and our 250+ employees enjoy up to two months of workation per year. We’ve also been recognised as a Top DACH Employer by Kununu for three consecutive years. Our mission is to make sustainable consumption the easy choice by enabling customers to buy products up to 40% cheaper while significantly reducing CO₂ emissions. If you thrive in an environment that values momentum, ownership, and impact, you’ll feel at home here. We’re a fast-paced, high-performance team that works hard and challenges itself everyday. To enable this high-performance every team member enjoys full autonomy over their location (we’re remote-first). Lead the design and delivery of AI-powered internal tools and systems that enable refurbed to operate as an AI-native company under our AI comfortable designing for scale, reliability, and cost on GCP Experience building AI/LLM-powered systems in production - from prototyping with model APIs through deployment, observability, and iteration Strong product instincts in the classic PM sense - has owned a product area end-to-end with discovery, PRDs, roadmap, success metrics, and measurable outcomes; not just "used AI tools as a backend engineer" Stakeholder management across senior leaders and department teams; able to align people around trade-offs and unblock cross-functional delivery Comfortable balancing IC engineering work with technical leadership: setting direction, reviewing designs, and mentoring others without losing hands-on fluency Deep, practical fluency with modern AI tooling and active engagement with the fast-moving ecosystem - has worked extensively with multiple coding assistants (e. g. Claude Code, Codex, Cursor), knows how to structure, build, and install skills/plugins/marke
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