AI Skill Engineer

Quadcode•Georgia, GA

4d•Remote

About The Position

We are Quadcode, a fintech company excelling in financial brokerage activities and delivering advanced financial products to our global clientele. Our flagship product, an internal trading platform, is offered as a Software-as-a-Service (SaaS) solution to other brokers. We're developing a next-generation IDE for multimodal AI generations and agentic scenarios. It's a full-featured platform that allows users to build complex AI solutions without deep infrastructure knowledge. Quadcode.ai is already available for download: https://quadcode.ai/ Skill Engineer — you are the architect of reusable AI components for the platform. You create ready-made "skills" that other users can embed into their projects. Your task is to develop, optimize, and scale solutions that work reliably and efficiently. This is a role for someone who understands the architecture of AI systems, can optimize prompts across different models, and anticipates edge cases.

Requirements

Technical education (completed or in progress) — CS, Engineering, Mathematics, Physics, or related field
Deep understanding of LLMs — how modern models work, their limitations and strengths; hands-on experience with ChatGPT, Claude, Gemini beyond casual use
Prompt engineering experience — not just writing prompts, but optimizing them, A/B testing, understanding how different parameters affect outputs
Python development — at a level sufficient for creating integrations, testing, and automation
Systematic and architectural thinking — ability to design scalable solutions and anticipate edge cases
Analytical approach — ability to measure, compare, and make decisions based on data
English B1+ — reading docs, API documentation, research papers
Self-sufficiency — doesn't require step-by-step instructions; can navigate unfamiliar systems independently

Nice To Haves

Experience with RAG (Retrieval-Augmented Generation) and vector databases (Pinecone, Weaviate, Milvus)
Familiarity with agentic frameworks (AutoGPT, LangChain, LlamaIndex patterns)
Fine-tuning experience or working with models through different APIs (OpenAI, Anthropic, Hugging Face)
Understanding of function calling and tool use in LLMs
Experience with evaluation frameworks for assessing AI output quality
Work with semantic search, knowledge graphs
Experimentation and metrics monitoring (latency, cost, quality)

Responsibilities

Develop ready-made skills — reusable components for common AI tasks (text analysis, classification, RAG, agentic workflows, etc.)
Optimize prompts across different models and scenarios; conduct A/B testing and measure output quality
Design RAG integrations and agentic pipelines — from architecture to implementation
Work with integrations — connecting external APIs, vector databases, knowledge sources
Test and document skills — create usage examples, handle edge cases, establish best practices
Analyze requirements and turn them into scalable components
Monitor skill performance and iterate based on feedback
Stay on top of AI trends and add new capabilities to the platform