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NEXTMOVEFDE careers · United States
Two Dots

Member of the Technical Staff - Chatbot Engineer

AI summary of the role

Two Dots is hiring a software engineer to build consumer-facing chat agents that serve as the frontend to complex workflows for their AI underwriting platform.

What you’ll do

  • Build consumer-facing chatbots that serve as the frontend to complex workflows
  • Bridge internal workflow APIs and domain object code with real-world call patterns of AI agents
  • Make smaller models perform like larger models
  • Design creative ways to automate product judgment, such as using chatbots to roleplay users

What you’ll bring

  • Strong Python ability (TypeScript or other strong software engineering backgrounds also welcome)
  • Deep understanding of context management, agent loops with tool calling, and prompt structure
  • Ability to build reliable systems manually, not just prompt through implementation
  • Comfortable using SQL or BigQuery to understand quality

Technologies

Python · TypeScript · SQL · BigQuery · LLM · chatbot · agent loop · tool calling · prompt engineering

About Two Dots

AI underwriting agent ("Eve") that automates income verification, identity checks, and fraud detection for multifamily property managers screening rental applicants.

Series A · 10–50 people

Source and classification

Production engineering · Evidence for this classification:

crisis and leaves people without the disposable income required to live satisfying lives, fueling resentment and political instability that turns problems at home into problems for the world. The Role Chat agents are becoming the primary interaction surface of the future. It sounds easy to make a good chatbot, but many systems fail because they misunderstand users, overfit prompts, hide structural problems, or turn complex workflows into brittle demos. We are looking for a software engineer who can build consumer-facing chat agents that serve as the frontend to complex workflows. This role requires a rare combination of user empathy, strong written English, strong Python ability, and a metrics-driven mentality. You should be comfortable using SQL or BigQuery to understand quality, but also know when to roll up your sleeves and do manual QA rather than treating every product problem
How jobs are selected

Employer postings · Data from · Sources