Full-Stack Engineer

• 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. 
  
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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.

• Interfaces & Build Tools - Vue 3 / React, TypeScript

• Core Frameworks - Node.js (LTS) + NestJS (core business logic), Python + FastAPI (AI services, orchestration, data processing)

• LLM & Orchestration - OpenAI, Anthropic, Google

•  Data Infrastructure - PostgreSQL, ClickHouse, Qdrant, Kafka, Redis, S3 / MinIO

• →Backend: deep expertise in Node.js and/or Python (FastAPI); solid grasp of asynchronous programming, RESTful APIs and microservice architectures.
  LLM integration: production experience building or supporting features on LLM APIs (Anthropic, OpenAI or similar) — structured outputs, retries and rate limits, streaming, fallbacks, and an understanding of token economics.
  Databases: strong PostgreSQL — query optimisation, execution plans, relational schema troubleshooting, transaction isolation levels.
  Debugging and observability: practical production troubleshooting with logs, metrics, distributed tracing (trace_id/request_id) and monitoring dashboards.
  Testing: Jest, Supertest or PyTest; robust regression tests; familiarity with evaluating non-deterministic (LLM) behaviour.
  AI-assisted development: daily fluency with agentic coding tools (Claude Code, Cursor or similar) as a normal working method, including judgement about when AI output needs verification.
• →LLM observability and evaluation tooling (Langfuse, prompt/trace platforms, eval frameworks).
  Docker and standard CI/CD pipelines.
  Queue systems or event-driven architectures (Kafka, RabbitMQ).
  Security hygiene: dependency vulnerability triage, secrets management.
• →Analytical, systematic debugging of unfamiliar codebases · systems thinking about how a small config, code or model change hits a broader ecosystem · full ownership from triage to production verification and post-mortem · clear stakeholder communication of root causes · Agile (Scrum/Kanban) with Jira and Confluence.

• 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).

• 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.

• Interview with HR
• Technical interview with team leaders