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Tech Stack
Tools & technologiesAWSCloudDistributed SystemsGoGoogle Cloud PlatformGraphQLJavaJavaScriptKubernetesNext.jsPythonReactTerraformTypeScript
About the role
Key responsibilities & impact- 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
- 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
Requirements
What you’ll need- 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.
- Master's or PhD in Computer Science, Machine Learning, or related field (preferred)
- Experience with AI agent frameworks (LangChain, LangGraph, or similar) and agentic development patterns (preferred)
- Experience integrating foundation model APIs (OpenAI, Anthropic/Claude, Google) (preferred)
- Familiarity with ML evaluation systems, including LLM-as-a-judge approaches (preferred)
- Experience with containerization and orchestration (Kubernetes), infrastructure-as-code (Terraform) (preferred)
- Background in building enterprise-grade internal tools and developer productivity platforms (preferred)
- Experience with frontend technologies (React, Next.js) for full-stack AI product development (preferred)
- Publications at top AI/ML venues a plus (preferred)
Benefits
Comp & perks- Bonus
- Equity
- Benefits
- Employee Travel Credits
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Large Language Models (LLMs)PythonTypeScriptGoJavaAPI designRESTGraphQLKubernetesTerraform
Soft Skills
collaborationinfluence without authoritycommunicationmentoringtechnical leadership
Certifications
BS in Computer ScienceMaster's in Computer SciencePhD in Computer ScienceMachine Learning
