Senior Fullstack/AI Engineer

OUR HIRING PROCESS: We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment. We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team. At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team. From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live. INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy We are looking for an experienced Senior Fullstack / AI Engineer who will be responsible for end-to-end feature development — from building intelligent AI agents on the backend to visualizing them through intuitive user interfaces. Why you’ll love this project: We have absolutely zero legacy code. Our entire stack is bleeding-edge (running the latest versions). We don’t just "plug in an OpenAI API key" — we are building a complex distributed system featuring RAG architecture, vector search, event streaming, and big data analytics. Our Tech Stack Frontend: Interfaces & Build Tools - Vue 3 / React, TypeScript Backend: Core Frameworks - Node.js (LTS) + NestJS (core business logic), Python + FastAPI (AI services, orchestration, data processing) AI & ML: LLM & Orchestration - OpenAI, Anthropic, Google Data Storage & Messaging: Data Infrastructure - PostgreSQL, ClickHouse, Qdrant, Kafka, Redis, S3 / MinIO Key Responsibilities Develop end-to-end functionality: from complex interactive interfaces and dashboards to distributed backend services using NestJS and Python. Design and maintain a microservices architecture, ensuring seamless interoperability between Node.js and Python services. Design and optimize data storage schemas across a heterogeneous environment (PostgreSQL, ClickHouse, Qdrant). Implement asynchronous inter-service communication and event streaming via Kafka. Integrate AI components, managing embeddings and semantic search functionality within Qdrant. Optimize application performance, build times, and data processing pipelines. Design and evolve the AI architecture: integrating OpenAI/Anthropic models, managing context windows, and optimizing token consumption ( tiktoken ). Build and tune RAG (Retrieval-Augmented Generation) pipelines using LangChain and Qdrant vector database. What We Are Looking For Experience Required: Senior, 4–5+ years in product development, with hands-on experience in LLM integration and data engineering Strong Fullstack Background: Deep knowledge of Node.js , Worker threads , and the NestJS ecosystem (solid understanding of Dependency Injection, Modules, Guards, Interceptors, and Pipes). Proficient in TypeScript (Vue 3, NestJS) and a proven track record of backend development with Python . Hands-on AI/LLM Experience: A solid understanding of prompt engineering, LangChain chains, embeddings, and semantic search. You know exactly how Claude differs from GPT in production environments. Vector DB Expertise: Practical experience with Qdrant (or similar vector databases) — including indexing, similarity search, and vector tuning. Data Infrastructure Literacy: Experience working with distributed systems, message brokers ( Kafka ), and analytical databases ( ClickHouse ). Database Mastery: You clearly understand when to query PostgreSQL, when to aggregate data in ClickHouse ( OLAP vs. OLTP ), and how vector indexes operate in Qdrant. Infrastructure Horizons: Experience with caching ( Redis ), object storage ( S3/MinIO ), containerization ( Docker/Kubernetes ), and the AWS ecosystem . Mindset: Strong analytical skills, a product-driven mindset, the ability to architect fault-tolerant systems, and a dedication to writing clean, maintainable code (SOLID, OOP/FP patterns). What We Can Offer You: Consistent monthly payment based on invoices (payments are made via bank transfer/ Payoneer or PayPal). Remote working from 14:00 to 23:00 EEST, including a one-hour break. Supportive work/life balance: paid vacation and sick leave. Opportunities for professional and career growth and development. Opportunity to use modern approaches and tools to solve business problems. Our recruitment process: Interview with HR Technical interview with team leaders