Software Engineer, New Hiring Experience, Express & Guide

About the NHX Express & Guide Team

The NHX Express & Guide team is reimagining how homeowners express problems and take action in the home services space. Our mission is simple but ambitious: help users feel seen, supported, and confident at every step of their journey from recognizing an issue to hiring the right professional. We’re building experiences that reduce uncertainty, clarify intent, and unlock forward momentum.

We’re an AI-native team at the core of Thumbtack’s product vision. We use multimodal inputs, Large Language Models (LLMs), and structured intelligence to transform how people describe home issues, troubleshoot needs, and discover solutions. Whether it’s interpreting a photo of a leaky faucet or guiding someone through a tricky repair with dynamic questions, we’re creating a new interaction layer that feels more like talking to a human than filling out a form.

The challenge

This is a unique opportunity to design a brand-new kind of experience that helps people care for their homes with more clarity, confidence, and ease. We’re not just layering in AI features, we’re rethinking the product from the ground up using LLMs, vision models, and agentic workflows to create smarter, more human interactions. The team moves fast, shipping real features and learning quickly through dual-track execution balancing short-term impact with long-term innovation. We focus on solving real-world problems with clarity, not just building flashy demos. If you're excited about using cutting-edge tech to make everyday life better, you’ll thrive here.

What you'll do

• Build and ship end-to-end product experiences that help users describe and solve home issues using AI-native interactions.
• Collaborate with designers, researchers, and product managers to prototype, test, and launch features that feel natural and support multimodality.
• Develop backend services and APIs that power intelligent intake flows, dynamic guidance, and personalized hiring suggestions.
• Integrate LLMs and vision models into user-facing experiences, applying techniques like context engineering, retrieval augmented generation, and structured memory.
• Own and improve systems that turn messy real-world input (like photos or voice notes) into actionable insights for our pros and users.
• Partner with infra and ML teams to monitor model performance, optimize latency, and drive continuous improvement in AI quality.
• Contribute to a culture of fast experimentation and thoughtful iteration, learning from every launch to improve both product and process

In order to be successful, you must bring

• 2+ years of experience in software engineering
• A strong passion for creating product experiences that genuinely delight users and improve their quality of life
• Curiosity and drive to stay on top of cutting-edge technology, with a habit of bringing those learnings into everyday work
• Hands-on experience building with AI whether through side projects, Vibe coding apps, or personal experiments, we’d love to see what you’ve built and hear how you approached it
• Fluent in at least one major programming language and would be able to switch between multiple languages. We mainly use Go, Python for our backend with Swift, Kotlin and Java for our mobile apps
• Familiarity with LLMs, machine learning frameworks, model performance monitoring & fine tuning
• Solid experience building software on top of relational & non-relational databases such as Postgres, MySQL, DynamoDB

Expected salary ranges

• For candidates living in San Francisco / Bay Area, San Jose, New York City, or Seattle metros, the expected salary range for the role is currently $169,600 - $219,500.
• For candidates living in Austin, TX or Washington DC metros or in California, Massachusetts, New Jersey, or Washington states, the expected salary range for the role is currently $152,700 - $197,600.
• For candidates living in all other US locations, the expected salary range for this role is currently $144,200 - $186,600.

Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role.