Member of the Technical Staff - Chatbot Engineer

About 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 like back-propagation. You are essentially a future version of a UX Engineer, but for conversational natural language experiences instead of buttons and forms.

Responsibilities

• Consumer-facing chatbots that serve as the frontend to complex workflows
• Bridging internal workflow APIs and domain object code with the real-world call patterns of AI agents
• Making smaller models perform like larger models
• Designing creative ways to automate product judgment, such as using chatbots to roleplay users instead of relying only on manual QA or fixed test cases
• Working closely with design and product to balance look and feel, interaction quality, and business objectives

Requirements

• You understand what belongs in tools and APIs versus what belongs in natural language. Designing that boundary should be a fixation for you.
• You also understand what is structural and what is in the domain of tone, framing, or model "dark magic." You care about the headspace the model is operating in, the quality of the user experience, and whether the product actually works for confused real people.
• Despite working on agents, you are not in "Gas Town." You do not believe every problem requires a meta-harness, and you do not outsource your judgment to chatbots. You know when to escalate to MLEs if a problem likely requires fine-tuning or more advanced methods.
• You care deeply about user outcomes. You measure how your experiments are doing, proactively solve quality problems, and have the frustration tolerance required for ambiguous chatbot engineering.
• The Team
• Other team members include: Meta ML alumnus with decades of experience, a 21 year old UMich grad who was a top 2,000 LoL player (he is no longer playing the game, thank god), and a former agave farmer who started a shipping and logistics company while at Stanford.
• Technical Fit
• Python is preferred. TypeScript or other strong softw

Additional Information

Company Mission / Why This Matters Two Dots builds verification and risk infrastructure for housing to help solve the housing crisis. Housing is too expensive because America created a single family mortgage machine to cut average people into home price inflation fueled by soft bans on new development. That worked for many decades, but when a small single family home costs several million dollars, it stops being an engine of opportunity and becomes a source of the very resentment modern mortgages were originally created to solve. Housing supply has been restricted so much that people have started fabricating documentation or relying on bypasses and overrides to sign up for a payment they can't really afford. That conceals the problem instead of solving it. We believe that public and private policy has to change, and that involves breaking the system that conceals our affordability 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.

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at two-dots? Share your experience