🇩🇪 Germany · 12h ago
Product engineer (AI-native)
qlaris.ai
LinkedInEnglish-friendly
All rolesEngineeringProduct engineer (AI-native)Berlin or remote (Europe) Full-timeReports Directly to CPTOThis is a senior engineering role with full product ownership. You will work directly with the founders, understand what users need, decide what to build, and ship it to production. The difference: you do this at 5-10x the throughput of a traditional engineer because you have rebuilt your workflow around AI agents, agentic coding tools, and LLM-assisted development. The practices you establish will define how the entire engineering team works as qlaris grows.What you would be buildingWe publish this because the right candidate evaluates the science, not just the pitch.qlaris is a synthetic consumer research platform: surveys, AI focus groups, and behavioral UX audits powered by psychometrically calibrated Synthetic Populations.Tech stack: Next.js 16, React 19, TypeScript (strict), Tailwind CSS v4, Cloud Firestore, Vertex AI Gemini, Anthropic Claude, Google Cloud Tasks, Browserbase + Stagehand for browser automation.Current product: 12 question types, AI-powered survey generation (3-agent pipeline), real-time streaming results, debate mode (AI focus groups), behavioral audits on live URLs, workspace collaboration, MCP server.The codebase is modern, well-structured, and already AI-friendly with comprehensive CLAUDE.md files, design tokens, and context layers. You would be productive on day one.What you will doEnd-to-end product engineeringOwn features from problem definition to production: talk to users, define scope, design the solution, write the code, ship it, measure itMake product decisions autonomously - you do not wait for a PM to write a ticket. You understand the user, the business, and the technical constraints, and you act on that understandingShip production-quality code daily, not weekly. The speed comes from AI-augmented workflows, not shortcuts on qualityAI-native engineering practicesUse Claude Code, Cursor, and agentic coding workflows as your primary development environment - not as an occasional assistDesign and maintain the context layers (CLAUDE.md, design tokens, architecture docs) that make AI tools effective across the teamBuild internal tooling, MCP integrations, and automation that multiplies the team's outputEstablish the engineering practices that new hires will learn - your workflow becomes the team standardProduct and user focusUse qlaris itself to validate product decisions before building - run concept tests, messaging checks, and feature prioritization with Synthetic PopulationsCollaborate directly with the founders on product strategy, roadmap prioritization, and GTMMaintain a short feedback loop between what you build and how users respond - analytics, support signals, and direct conversationsWhat you bringRequiredStrong software engineering foundation: CS degree or equivalent depth, 4+ years of professional software development experienceDemonstrated product sense: you have shipped features that users loved, not just features that worked. You can explain why you built what you built, not just how.Proficiency with modern web stack: React, TypeScript, Node.js, Firestore or similar NoSQL. Our stack is Next.js + React 19 + Tailwind.Daily, productive use of AI coding tools: Claude Code, Cursor, Copilot, or equivalent. You should be able to describe specific workflows where AI agents made you meaningfully faster, not just "I use Copilot for autocomplete."Ability to work autonomously in an early-stage environment: low process, high ownership, direct founder accessStrong written communication: you document decisions, write clear PRs, and communicate asynchronouslyStrong differentiatorsExperience building agentic workflows or MCP integrationsTrack record of shipping consumer-facing products at startupsFamiliarity with LLM APIs (Anthropic, OpenAI, Google Vertex AI) and prompt engineeringPrevious experience as a founding or early engineer where you shaped the engineering cultureBackground in research tools, data products, or developer toolsNot requiredA specific number of years of experience - we care about what you can ship, not when you startedManagement experience - this is a hands-on building roleA portfolio of open source contributions - shipping product matters more than side projectsWhat we offerDefine AI-native engineering from the ground upYou are not adopting someone else's best practices. You are creating them. The workflows, tooling, and development culture you establish will be what every future engineer at qlaris learns.Full product ownershipNo handoffs between PM, design, and engineering. You own the feature from idea to production. This is how the best products get built - by engineers who understand users.Direct founder accessYou work with both founders daily. No layers, no translation loss. Your judgment shapes the product.Meaningful equityYou are building core product at an early stage. Your compensation reflects that.Competitive salaryWe pay well. Early stage does not mean below market.Full flexibilityBerlin hybrid or fully remote within Europe. Measured on output, not office hours.A real AI-native codebaseThis is not a legacy codebase where you fight the code to use AI. The codebase was built for AI-assisted development from day one: comprehensive context files, design tokens, structured data, clear architecture.Why this role is differentMost companies hiring "AI engineers" want someone to build AI features. We want someone who uses AI to build everything faster. The distinction matters: you are not a machine learning engineer. You are a product engineer whose entire workflow is AI-augmented - from understanding the problem to shipping the solution. This role is for someone who has already made that shift and wants to make it the standard.Apply for this roleNo cover letter template needed. Just your details and a link to your work.Name *Email *LinkedIn profile or link to CV *All rolesEngineeringProduct engineer (AI-native)Berlin or remote (Europe) Full-timeReports Directly to CPTOThis is a senior engineering role with full product ownership. You will work directly with the founders, understand what users need, decide what to build, and ship it to production. The difference: you do this at 5-10x the throughput of a traditional engineer because you have rebuilt your workflow around AI agents, agentic coding tools, and LLM-assisted development. The practices you establish will define how the entire engineering team works as qlaris grows.What you would be buildingWe publish this because the right candidate evaluates the science, not just the pitch.qlaris is a synthetic consumer research platform: surveys, AI focus groups, and behavioral UX audits powered by psychometrically calibrated Synthetic Populations.Tech stack: Next.js 16, React 19, TypeScript (strict), Tailwind CSS v4, Cloud Firestore, Vertex AI Gemini, Anthropic Claude, Google Cloud Tasks, Browserbase + Stagehand for browser automation.Current product: 12 question types, AI-powered survey generation (3-agent pipeline), real-time streaming results, debate mode (AI focus groups), behavioral audits on live URLs, workspace collaboration, MCP server.The codebase is modern, well-structured, and already AI-friendly with comprehensive CLAUDE.md files, design tokens, and context layers. You would be productive on day one.What you will doEnd-to-end product engineeringOwn features from problem definition to production: talk to users, define scope, design the solution, write the code, ship it, measure itMake product decisions autonomously - you do not wait for a PM to write a ticket. You understand the user, the business, and the technical constraints, and you act on that understandingShip production-quality code daily, not weekly. The speed comes from AI-augmented workflows, not shortcuts on qualityAI-native engineering practicesUse Claude Code, Cursor, and agentic coding workflows as your primary development environment - not as an occasional assistDesignSourced from LinkedIn. Relocantly aggregates public job postings; apply on the original site.