We’re looking for a hands-on Full-Stack AI Engineer who builds real, production-grade AI systems, not demos, to join our financial partner’s team.

Projects

Call Center Intelligence: Whisper-based transcription with LLM post-processing, task extraction, and Teams Bot integration

Document Understanding: RAG pipelines with DSPy optimization for financial document Q&A

Multi-Agent Workflows: Autonomous agents that handle complex, multi-step financial processes

AI-Powered Internal Tools: Chat interfaces (Chainlit, custom React) that boost team productivity

This is a hybrid role for people who refuse to be boxed in. Some weeks you'll be knee-deep in RAG pipeline optimization. Others, you'll be building the React interface that makes that intelligence accessible to humans. We need T-shaped engineers who go deep in one area while staying dangerous across the full stack.

On the AI Side

Design and build production RAG pipelines—chunking strategies, embedding models, vector databases (Pinecone, Weaviate, ChromaDB), and retrieval optimization
Architect multi-agent systems using LangGraph and LlamaIndex for complex financial workflows
Fine-tune open-source LLMs (Llama, Qwen, Mistral) for domain-specific tasks when API calls aren't enough
Build AI microservices in Python/FastAPI that serve models with sub-second latency
Implement evaluation frameworks (DSPy) to measure and improve model performance systematically

On the Product Side

Build responsive frontends in React (Next.js) and TypeScript that make AI features intuitive
Develop backend services in Node.js/NestJS or Python that orchestrate AI capabilities with business logic
Own the full lifecycle: you build it, you deploy it, you monitor it, you improve it
Work directly with product managers to translate business problems into technical solutions

Stack

Cloud: Azure (AKS, Azure OpenAI Service), Docker, Terraform
AI/ML: PyTorch, Hugging Face, LangChain, LlamaIndex, DSPy, Whisper
Backend: Python (FastAPI), Node.js/TypeScript (NestJS)
Frontend: React (Next.js), TypeScript
Data: PostgreSQL, Vector DBs (Pinecone, Weaviate, ChromaDB)
Observability: Prometheus, Grafana, Loki

Requirements

4+ years of production software engineering experience
Strong Python skills (you can write clean, testable, production-ready code)
Hands-on experience with at least one GenAI stack (LangChain, LlamaIndex, or similar)
You've built and deployed web applications—frontend or backend, ideally both
You can explain complex technical concepts to non-technical stakeholders

Plus

Experience with RAG systems in production (not just tutorials)
You've fine-tuned LLMs for real use cases
Background in fintech, banking, or high-stakes production systems
MLOps experience (model monitoring, A/B testing, deployment pipelines)
Contributions to open-source AI projects

What we offer

Hybrid, Budapest
1.900.000 - 3.000.000 HUF/Month (The salary range may be adjusted upwards based on seniority and relevant experience.)
Real ownership: you build it, you run it.
Fast-moving fintech environment with flat hierarchy.
Best-in-class tools: Jira, Confluence, Miro, Figma, ChatGPT, modern cloud services.
Skilled teammates, open debate, supportive culture.
Training, workshops, and conferences to stay ahead in AI.