About The Position

Candid is collapsing pre-construction engineering for large compute and energy infrastructure projects. Today, critical work lives inside complex diagrams, specs, and technical documents and is still done manually. We’re building systems that can understand this data, structure it correctly, and execute workflows like design review, comment resolution, and technical bid evaluation.

Requirements

  • Python
  • PyTorch
  • multimodal LLMs
  • open-source VLMs (Gemma, Qwen, DeepSeek, etc)
  • LangGraph
  • PydanticAI
  • custom state machines
  • Graph databases (Neo4j)
  • vector databases

Nice To Haves

  • Strong opinions about system design, even when tradeoffs aren’t obvious
  • Cares deeply about keeping the codebase clean and understandable
  • Feels physical discomfort when seeing inefficient code or fragile architectures
  • Has good intuition when designing new systems without a spec
  • Cares about taste, clarity, and building things that feel right, not just things that work
  • Early or founding engineer at a YC-backed company
  • Experience with document intelligence, vision pipelines, or agent-based systems
  • Built something from scratch that real users depended on
  • Technical founder at a VC-backed startup

Responsibilities

  • Build vision pipelines that extract structure, entities, and spatial relationships from engineering diagrams and documents.
  • Design agentic systems that decompose large pre-construction tasks into discrete, verifiable steps.
  • Build human-in-the-loop flows to capture expert feedback and improve system correctness.
  • Own systems end-to-end, from raw inputs to structured outputs used in production workflows.
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