Senior Software Engineer, AI Products

Airbnb

6d•Remote

About The Position

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join The Airfam Products team exists to make every Airbnb employee more productive through a unified digital headquarters experience. As part of a 13-person cross-functional team of engineers, designers, researchers, and product managers, you'll work on platforms that serve Airbnb's entire global workforce. Our portfolio includes One Airbnb (the company's internal cultural hub with enterprise search, people profiles, and AI-powered chat), OneChat (Airbnb's enterprise AI assistant enabling secure LLM interactions), and a suite of tools that power how employees discover information, connect with colleagues, and get work done. You'll be joining the AI for Non-Developers workstream, focused on expanding AI productivity tools to all Airbnb employees—building OneChat Agents, deep research capabilities, artifact creation tools, and task automation that make AI accessible to everyone, regardless of technical background. The Difference You Will Make As a Senior Software Engineer on the Airfam Products team, you'll be instrumental in building Airbnb's next generation of AI-powered employee experience platforms. Your work will be a force multiplier for the entire company—every AI feature you ship, every system you architect, and every engineer you mentor will amplify productivity across Airbnb's global workforce. You will: Democratize AI by building tools that empower non-technical employees to leverage the power of LLMs Drive innovation by taking AI prototypes from concept to production at scale Shape the future of how Airbnb employees work, collaborate, and discover information

Requirements

8+ years of software engineering experience, with significant focus on building production AI/ML systems
Deep understanding of Large Language Models (LLMs) including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG)
Strong proficiency in Python and at least one additional language (TypeScript, Go, or Java)
Experience building and deploying production ML systems at scale with high availability and low latency requirements
Strong backend and distributed systems expertise, including API design (REST, GraphQL) and cloud infrastructure (AWS, GCP)
Track record of shipping AI-powered products from prototype to production
Proven ability to collaborate cross-functionally and influence without authority
Excellent communication skills with ability to distill complex technical concepts for diverse audiences
BS in Computer Science, Engineering, or equivalent practical experience

Nice To Haves

Master's or PhD in Computer Science, Machine Learning, or related field
Experience with AI agent frameworks (LangChain, LangGraph, or similar) and agentic development patterns
Experience integrating foundation model APIs (OpenAI, Anthropic/Claude, Google)
Familiarity with ML evaluation systems, including LLM-as-a-judge approaches
Experience with containerization and orchestration (Kubernetes), infrastructure-as-code (Terraform)
Background in building enterprise-grade internal tools and developer productivity platforms
Experience with frontend technologies (React, Next.js) for full-stack AI product development
Publications at top AI/ML venues a plus

Responsibilities

Lead the technical design and implementation of LLM-powered features for OneChat and enterprise AI tools, including RAG pipelines, agent orchestration, and prompt optimization
Partner with product managers, designers, and cross-functional teams to translate user problems into AI-powered solutions that serve Airbnb's global workforce
Architect and build production-ready AI/ML-integrated systems, ensuring scalability, reliability, and low latency across multi-cloud environments
Develop and iterate on agentic AI capabilities, including multi-step reasoning, tool use, and context-aware decision-making
Implement evaluation pipelines and quality systems to measure model performance, safety, and user satisfaction
Own production AI systems end-to-end, including deployment strategies, monitoring, alerting, and incident response
Collaborate with the DevAI team on AirChat SDK integrations, MCP (Model Context Protocol) implementations, and Glean Action Packs
Mentor engineers (L6-L8) through design reviews, architecture discussions, and pair programming sessions
Stay current with emerging AI technologies and evaluate their applicability to employee experience products
Balance hands-on technical contributions with technical leadership activities