LLM Solutions at Byborg
Shipped production AI systems for millions of users. Prompt engineering, agent design, stakeholder communication.
Role & Context
Context & Prompt Engineer / LLM Engineer
Byborg Sárl
Agentic LLM systems, multimodal tooling, and production-scale deployment.
Large-scale LLM and multimodal systems for consumer platforms.
The Challenge
Byborg needed production LLM systems that could handle millions of users. The work required sophisticated prompt engineering, context management, multimodal integration (text + image), and real-time moderation. Performance, safety, and user experience all had to work at scale.
Note: This project involved AI solutions for adult entertainment platforms. The work focused on technical implementation and system architecture. All development followed appropriate professional and ethical standards.
What I Did
Stakeholder Work
- Partnered with product and business teams to translate requirements into AI capabilities
- Presented trade-offs to non-technical stakeholders (latency vs quality, safety vs creativity)
- Coordinated with engineers on integration, monitoring, and deployment
- Delivered regular updates on progress, blockers, and decisions
Technical Work
- Designed prompt architectures for complex conversational AI
- Built context management and memory systems for long-form interactions
- Integrated multiple LLM models (Gemma, QWEN, custom fine-tuned)
- Created ComfyUI workflows for image generation
- Implemented safety protocols and content moderation
Key Results
- Deployed to multi-million-user platform portfolio
- Shipped features on schedule with agreed success metrics
- Maintained performance and safety standards at scale
Tech Stack
Python, LangChain, LangSmith, ComfyUI, Visualis, Flowise, SDXL