O pozici
GR8 _TECH builds B2B iGaming platforms for operators who play to lead.
We deliver full-cycle, high-impact tech designed to scale — from seamless integrations and expert consulting to long-term operational support. Our platform powers millions of active players and drives real business growth. Call it what it is: the iGaming Platform for Champions.
With 1000+ GR8 people across locations and time zones, we don’t just ship technology — we help operators build success stories across brands, markets, and geos.
Our ambition drives us. Our people make it real.
If you’re a challenger in spirit and a champion in action — join us.
Co budeš dělat
- Own LLM-based systems from design to production support.
- Design architectures for Generative AI systems (RAG, agents, tool/context serving).
- Make clear trade-offs between quality, latency, cost, and complexity.
- Set engineering standards for building and operating AI systems in production.
- Act as a technical reference point for applied GenAI.
- Build and maintain production LLM-powered systems.
- Develop chatbots and AI assistants with predictable behavior.
- Design and implement RAG pipelines (ingestion, embeddings, retrieval, generation).
- Implement agent-style workflows with tool/function calling.
- Build and integrate MCP servers or similar context/tool-serving components.
- Integrate AI systems with backend services and ML infrastructure.
- Design evaluation frameworks for LLM outputs.
- Monitor LLM behavior, system health, and costs in production.
- Address performance, scalability, and operational issues.
- Handle production incidents and contribute to long-term fixes.
- Design systems with failure modes, fallbacks, and graceful degradation.
Koho hledáme
- Strong software engineering background.
- Proven experience building LLM-based systems in production.
- Hands-on experience with: LLMs and RAG architectures, Chatbots or conversational AI systems, Tool/function calling and agent-style patterns.
- Experience with context or tool-serving systems (MCP or similar).
- Experience integrating AI into real-time production products.
- Understanding of performance, scalability, and cost trade-offs.
- Cloud experience (preferably AWS).
- Strong engineering fundamentals (testing, debugging, reviews, observability).
Benefity
- Benefits Cafeteria — annual budget you allocate to:
Sports • Medical • Mental health • Home office • Languages.
- Paid maternity/paternity leave + monthly childcare allowance.
- 20+ vacation days, unlimited sick leave, emergency time off.
- Remote-first + tech support + coworking compensation.
- Team events (online/offline/offsite).
- Learning culture with internal courses + growth programs.