HRAVITY
AI

AI engineer Python LLM

HRAVITY · Українка, AI, UA

Actively hiring Posted about 2 hours ago

Role overview

COMPANY

Arcyn is a freshly funded pre-seed stage startup. We’re creating an AI-powered compliance checker for architectural design — an Autodesk Revit plugin that automatically checks designs against regulations as they’re being created. Architects get instant feedback on violations as they design in Revit, instead of waiting weeks for permit reviewers to tell them what’s wrong.

We’ve just closed pre-seed round and are building core technical team. We’re now a team of 4 with a track record of building complex technical products, and we’re looking for a strong AI engineer who’s comfortable testing hypotheses and working across different frameworks. This is a chance to join at the ground floor, shape product architecture and solve genuinely hard AI problems.

What you'll work on

  • Design and maintain modular, multi-step AI workflows for compliance automation.
  • Integrate multiple LLM providers (e.g., OpenAI, Anthropic, Perplexity) into a cohesive orchestration pipeline.
  • Build cost-optimized batch processing and intelligent API request strategies.
  • Translate complex regulations into structured, machine-executable logic.
  • Develop and validate automatically generated code to ensure correctness, safety, and performance.
  • Collaborate with domain experts to refine logic interpretation and edge case handling.
  • Maintain high-quality, well-structured Python codebases with clear separation of concerns.

What we're looking for

  • 5+ years of professional software engineering experience.
  • Strong Python skills, including experience writing production-grade, modular code.
  • Proven track record building multi-step LLM workflows (LangChain, LangGraph, or similar).
  • Experience in structured code generation and validation.
  • Strong debugging skills and comfort working with complex, evolving systems.

Nice-to-have:

  • Experience with compliance automation, technical regulations, or domain-specific rule translation.
  • Familiarity with Pydantic models or other type-safe data management frameworks.
  • Background in developer tooling or systems requiring high reliability and reproducibility.
  • Experience optimizing LLM API usage for both cost and speed.

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