Senior Full-Stack Engineer (Applied AI) at Sagan Recruitment | Torre

Senior Full-Stack Engineer (Applied AI)

You'll architect AI-powered productivity tools, shaping the future of work for Scandinavian businesses.
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Full-time
Compensation
USD3.2K - 5K/month
Non-negotiable
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Remote (for Poland residents)
Remote (for Romania residents)
Remote (for South Africa residents)
Remote (for Argentina residents)
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Posted 2 months ago

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Location: Remote (Strong preference for CEE or Africa) Salary Range: 3200 - 5000 EUR/month Work Schedule: Monday - Friday, 9:00 AM to 5:00 PM (CET) NOTE: INDEPENDENT CONTRACTOR POSITION Company Overview: Sagan is an exclusive membership community for top executives, founders, and CEOs seeking to hire and maximize the impact of international talent. We bridge the gap between global talent and US-based businesses, connecting candidates from vibrant regions like Latin America, the Philippines, India, Pakistan, Bangladesh, and Africa with leading American companies. Sagan provides a high-performance remote work environment, ensuring access to world-class opportunities for top-tier professionals. About the Company: Sagan represents a European AI/ML software agency and product company building productivity tools for Scandinavian businesses. The team works across diverse sectors but is typically brought in when traditional automation and simple wrapper-style AI solutions are not sufficient. Alongside client work, the company is developing reusable modules and infrastructure, and has a SaaS launch planned for 2026. The environment is highly technical, collaborative, and optimized for asynchronous, remote work. writing-driven. All team members work autonomously, communicate clearly, and take ownership from concept to deployment. Position Overview: We’re hiring a Senior Full‑Stack Engineer (Applied AI) to design and build full‑stack applications that heavily integrate LLMs. You’ll work on chat interfaces, end‑to‑end AI‑assisted products, durable workflows, document‑processing pipelines, structured‑output UIs, and retrieval‑augmented features. Current initiatives include new AI interaction patterns embedded in text editors and pipelines that validate thousands of documents against authoritative sources such as building codes and legislation. In this senior engineering role, strong product thinking, clear communication, and the ability to turn ambiguous problems into shippable solutions are essential. Key Responsibilities: Build modern, responsive, full-stack web applications using TypeScript, Node.js, and React. Implement APIs, asynchronous tasks, pipelines, and backend services (mainly with Postgres). Design and consume APIs (primarily GraphQL, with some REST). Integrate LLM-powered features, including: >> Structured outputs >> Multi-step workflows >> Tool-use patterns >> Context management >> Streaming responses Write clear, structured technical documentation and feature specifications. Own projects from scoping → development → deployment. Break large initiatives into deliverable chunks. Propose and advocate for sound technical solutions. Communicate effectively in a primarily async environment. Coach and unblock junior colleagues as needed. Qualifications: Excellent command of TypeScript, Node.js, and React. Proven experience building modern frontend applications. Strong backend development experience: APIs, async processing, pipelines, Postgres. Experience designing and consuming GraphQL APIs. Clear technical communication,. written and verbal. Ability to work independently and handle shifting requirements. Demonstrated ownership mindset with a focus on outcomes. Working knowledge of LLM integration patterns (does not need to be deep; curiosity and hands-on exploration are more important). Nice-to-Haves: Experience with ReScript or functional programming. Familiarity with Effect. Event-sourcing experience. Experience with Kafka Experience with block editor frameworks (BlockNote, Slate/Plate, Tiptap). Experience with Mastra or similar agent frameworks. Background with Temporal or other workflow orchestrators. CI/CD setup experience. DevOps experience (Railway, Koyeb, GPU serverless compute). Python or FastAPI knowledge. Exposure to data science, ML, or fine-tuning. Experience using stacked PRs (Graphite). Knowledge of vector embeddings, full-text and similarity search, retrieval pipelines, re-ranking. Experience with LLM observability tools: tracing, evals, prompt versioning.
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