Requirements
- Have a strong interest in AI, especially enterprise AI solutions, and genuine enthusiasm to learn and keep pace with the latest developments and trends.
- Bring a strong engineering background, with hands-on experience building and deploying AI, ML, or LLM-based systems.
- Have experience designing platform-level capabilities (APIs, SDKs, shared services) that other engineering teams consume.
- Are comfortable working across teams, explaining trade-offs, mentoring others, and partnering with various stakeholders.
- Have a practical understanding of modern AI tooling: LLM APIs, vector stores, RAG, evals, agent frameworks, and developer assistants such as Cursor.
- Understand software architecture and version control (Git), whether from a development background or equivalent hands-on AI experience.
- Bring a pragmatic, delivery-focused mindset; comfortable in a large, regulated, multi-product engineering environment.
Nice to Have
- Familiarity with Google Cloud AI services (Gemini Enterprise Agent Platform, ADK)
- AI evaluation or AI security experience.
- Agentic development experience (MCP, multi-agent systems).
- RAG implementation experience.
- Cloud DevOps or Terraform experience.
- Prior experience in iGaming, fintech, or another regulated industry.
- AI governance experience or interest.
- Coding experience, especially in Python
Benefits
- Hybrid working style – work in our modern and comfortable office as well as work from home office.
- Neat benefits & bonus package.
Work Arrangement
Hybrid
