Senior Frontend Engineer

Summary

Join Thumbtack's NHX Express & Guide team and help reimagine how homeowners express and address home issues. The team is building AI-native experiences to reduce uncertainty and guide users from problem recognition to hiring professionals. You will design and build end-to-end product experiences using AI-native interactions, collaborating with designers, researchers, and product managers. Responsibilities include developing backend services and APIs, integrating LLMs and vision models, and improving systems that process real-world input. The team values fast experimentation and thoughtful iteration, focusing on solving real-world problems. This is a unique opportunity to leverage cutting-edge technology to improve everyday life.

Requirements

• 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

Responsibilities

• 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