About SimplicityDX

SimplicityDX (SDX) converts creator user-generated content (UGC) into structured, verified, agent-readable social proof for AI-powered commerce. We operate as infrastructure for the agentic commerce era, not as a content or marketing tool.

Our platform began by solving a real-time problem for the creator economy: as a creator’s post goes live, SDX ingests it, matches it against the brand’s product catalogue and the creator’s own media, and assembles a purpose-built storefront on the fly. The creator gets a single link to drop into their social call-to-action, and that link resolves to a shoppable experience built for that exact post.

We are now extending that same ingestion, verification, and assembly capability to a bigger problem: AI shopping agents (ChatGPT Shopping, Google AI Mode, Perplexity, Gemini, and the frameworks that will follow them) can already retrieve structured product data — price, specs, availability. What they cannot do reliably is judge whether a product works for a specific person or use case. SDX’s verified creator UGC is built to close that gap: human-validated evidence, creator context, and use-case-specific claims that an AI agent can reason over rather than merely retrieve. Our mission is to make verified, trustworthy UGC a standard, queryable layer of the agentic web — available not just on our own storefronts, but to any AI chatbot or agent that shops on a consumer’s behalf.

Why Lisbon

Lisbon is our first office outside our current base, and this hire is one of the founding members of that team.

Early engineers here will have an outsized hand in how the office’s engineering culture, standards, and working practices take shape.

What You’ll Work On

SDX engineers work across a pipeline that runs from raw creator content to something an AI agent can trust and act on. Depending on the role, that includes:

Real-time ingestion — pulling and normalizing creator content across heterogeneous, constantly changing social platform APIs.

Claim and evidence extraction — turning creator speech and video into structured, verifiable product claims, and linking each claim to the specific timestamped clip that supports it.

Verification infrastructure — the pipelines and tooling behind our multi-layer human verification process, which produces the confidence signals that make our data trustworthy to both shoppers and AI agents.

Storefront and evidence-page assembly — dynamically building shoppable storefronts and structured evidence documents (schema.org, custom SDX schema types) from a blend of brand catalogues and creator UGC.

Distribution to AI surfaces — exposing verified UGC through commerce feeds (e.g. Google Merchant Center) and through direct agent-facing interfaces such as MCP (Model Context Protocol) endpoints, so AI shopping agents can query our data at inference time.

This is genuine infrastructure work — real-time systems, structured data and schema design, integrations with commerce and social platforms, and building for consumption by AI agents rather than only human browsers — not content tooling or campaign management.

How We Work: Embracing an AI-Native Engineering Culture

SDX is deliberately building an AI-native engineering culture, and we want that reflected in how the team works day to day, not just in what we build for customers.

We expect engineers to work comfortably with an AI coding agent that is integrated directly into our codebase and issue tracker — using it to scaffold, implement, refactor, investigate, and triage as a normal part of the job, not as a novelty.

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