{"id":3861833,"url":"https://alion.io/job/embedl-full-stack-developer","title":"Full Stack Developer","company":{"id":720205,"name":"Embedl","domain":"embedl.com","url":"https://alion.io/company/embedl-2","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gothenburg, Sweden"],"countries":["SE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Node JS","optional":false},{"name":"Python","optional":false},{"name":"Svelte","optional":false},{"name":"SvelteKit","optional":false},{"name":"TypeScript","optional":false},{"name":"AI Agents","optional":true},{"name":"Git","optional":true},{"name":"GitHub","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"Physical AI","optional":true},{"name":"Playwright","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prisma","optional":true},{"name":"React.js","optional":true},{"name":"SQL","optional":true},{"name":"Tailwind CSS","optional":true},{"name":"Vitest","optional":true},{"name":"Vue.js","optional":true}],"status":"live","first_seen_at":"2026-11-06T07:07:35Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-06T17:28:34Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About Embedl and the Hub\nEmbedl builds tools that help engineers develop and deploy AI on physical hardware. Embedl Hub is our developer platform for engineers and organizations, bringing data visualizations, experiment tracking, models, hardware results and validation evidence together to help teams understand results and decide what to do next. Our ambition is to become a leader in physical AI, a rapidly developing field bringing intelligence into real-world machines. You will help build the developer tools that make this possible.\nThe role\nWe are looking for a full stack engineer with at least three years of professional experience who loves finding user problems and building something useful to solve them. You will drive work from discovery through system design, backend and frontend implementation, and production.\nYou take the initiative to talk to users, understand where they get stuck, and turn what you learn into a small MVP you can ship quickly. You follow up to find out whether it helped, then improve it or change direction. You care about what users achieve with your work.\nYou have already made AI coding agents part of your development process. You know how to give them useful context, delegate well-scoped work, and review and test the results. You remain accountable for the design and code you deliver.\nYou will join a team that values collaboration and teamwork. You will also work closely with ML engineers and learn directly from customers. The Hub is primarily deployed in customer-controlled environments, so installation, upgrades and operation matter alongside the product experience.\nWhat you will do\n· Build relationships with users, observe their workflows and investigate recurring frustrations. Propose problems worth solving and agree priorities with the team.\n· Choose the smallest useful MVP and get it into users’ hands quickly. Keep the scope focused while protecting their data and existing workflows.\n· Define success before building. After release, combine user feedback with evidence such as adoption, task completion or time saved to decide whether to iterate, expand or stop.\n· Design systems across the stack: service boundaries, APIs, data models and frontend flows. Explain tradeoffs around simplicity, performance, security and maintainability.\n· Build backend services, database schemas and integrations with Python tooling and hardware execution systems.\n· Build clear, accessible interfaces for technical users working with experiments, model lineage, hardware results and validation evidence.\n· Use coding agents for implementation, investigation, testing and review. Improve the context, instructions and checks that make these workflows reliable.\n· Own reliability and performance for the features you ship, including observability, debugging and production fixes. Contribute to code review and CI/CD.\nOur stack\nThe Hub application uses TypeScript and SvelteKit on Node.js, with PostgreSQL and Prisma for data, and Tailwind CSS for the interface. Python supports SDKs and ML integrations. We use Docker, CI/CD, Vitest and Playwright. You should be comfortable learning across this stack; experience with every tool is not required.\nWhat you bring\n· 3+ years of professional software engineering, including building and maintaining web apps in production.\n· Initiative across frontend and backend: you’ve spotted a user problem, shipped a first version and learned from what happened next.\n· Practical system design: you turn vague requirements into workable designs and can explain the tradeoffs.\n· Strong TypeScript and a modern frontend framework. Svelte/SvelteKit is a plus; React, Vue or similar also transfers.\n· Backend experience: API design, SQL, relational data modeling, authentication and authorization. You’re comfortable with Node.js, or happy to learn it.\n· Agentic development workflows in real projects: you scope tasks, provide context, review changes and catch incorrect or insecure output.\n· Automated testing, Git, Docker and CI/CD, and you can debug issues from the application through to deployment.\n· You make progress when the problem is still unclear, ask for help when you need it and change your mind when the evidence says so. Clear English; Swedish is a plus.\nUseful additional experience\n· Python, ML tooling, experiment tracking, model registries, hardware benchmarking or physical AI.\n· Developer tools, data visualization or products for technical users.\n· Customer-managed deployments, Kubernetes, infrastructure as code or environments with restricted network access.\n· Traceability, validation or engineering workflows in regulated industries.\nWhat we offer\nYou’ll shape what we build and how it feels to use. You’ll help decide which user problems the Hub should solve, and you’ll have a real say in both its architecture and its user experience. Your teammates are experts in ML, compilers and hardware, and together we build the tools engineers use to bring AI into the physical world. We are team that likes working together and means it, we assume good intent, say what we think, and don't let disagreements get personal. Real acceptance of each other's differences, not just tolerance of them. A seat at the table on how this company is built, and room to keep learning.\nHealth and wellness allowance (friskvårdsbidrag) of 5000 SEK, wellness hour (friskvårdstimme), and private health insurance.\nHow to apply\nApply with your CV and a short example of a user problem you took ownership of. What did you ship first, how did you judge whether it worked, and what did you change after learning from users? Include how coding agents contributed to your work. A GitHub link or portfolio is welcome but not required; please avoid sharing confidential code or customer information.\nApplication Process\nThe selection and interview process is ongoing so please send your application in English as soon as possible via our website. The application will close on the 30th of November.\nIf you have any questions, please send them to Ann Tornberg at .\nYou're welcome at Embedl for who you are, no matter where you come from, what you look like, or what your favorite IDE is. 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