Tech Stack

Description

As a Senior Software Engineer on the Airfam Products team, you will build the next generation of AI-powered employee experience platforms at Airbnb, including AI chat tools and agents that empower all employees to leverage LLMs. You will lead technical design, implement LLM-powered features, and mentor engineers to amplify productivity across the global workforce.

Requirements

• 8+ years of software engineering experience, with significant focus on building production AI/ML systems
• 2+ years of hands-on experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, embeddings, and RAG
• Strong proficiency in backend technologies (TypeScript, Go, or Java)
• Strong backend and distributed systems expertise, including API design (REST, GraphQL) and cloud infrastructure (AWS, GCP, or Azure)
• 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
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• Preferred: Master's or PhD in Computer Science, Machine Learning, or related field
• Preferred: Experience building AI agents and multi-agent systems, preferably using Claude
• Preferred: Experience building integrations using MCP
• Preferred: Experience with containerization and orchestration (Docker, Kubernetes)
• Preferred: Background in building enterprise-grade internal tools
• Preferred: Experience with frontend technologies (React, Next.js)
• Preferred: Contributions to open-source Gen AI/ML projects or publications

Responsibilities

• Lead the technical design and implementation of LLM-powered features for OneChat and enterprise AI tools, including RAG pipelines, AI agents, and prompt optimization
• Partner with product managers, designers, and cross-functional teams to translate user problems into AI-powered solutions
• 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, detect hallucinations, and ensure responsible AI practices
• 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 implementations, and Glean Action Packs
• Mentor engineers through design reviews, architecture discussions, and pair programming sessions
• Stay current with the GenAI landscape, evaluating new models and techniques for potential application