Senior Software Engineer -Payments at Airbnb

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

15 May, 26

Salary

0.0

Posted On

14 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Backend Engineering, Platform Engineering, Data Engineering, AI Frameworks, LangGraph, Strand, Airflow, Kubeflow, Kafka, Spark, Ray, Observability, Model Governance, Performance Optimization, Vector Search

Industry

Software Development

Description

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 Payments AI/ML Foundation team builds the shared platforms, services, and guardrails that enable product and data teams across Airbnb Payments to deliver trustworthy, efficient, and scalable AI capabilities. We provide the infrastructure for training, evaluation, inference, and operations - covering model lifecycle, observability, governance, cost/latency optimization, and developer ergonomics - so teams in Payments can move quickly in AI innovation with confidence. The Difference You Will Make: As a Senior Software Engineer on Payments AI/ML Foundation, you will design and own core platform components that power AI across Airbnb Payments. You will partner with product, infra, data science, and operations to translate ambiguous requirements into robust systems with clear SLAs; build tooling and automation that makes AI development safer and faster; and raise the bar on reliability, performance, and governance for models and agents in production. A Typical Day: Envision, champion, and support the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems. Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for AI/ML models, drive engineering decisions, and quantify impact. Hands-on productionize and operate AI/ML solution and pipelines at scale, including both batch and real-time use cases. Lead, mentor, challenge and grow enthusiastic, collaborative AI/ML culture within the organization Your Expertise: BE/B.tech, preferably in CS, or equivalent qualification. 7+ years of industry experience in backend/platform engineering (or equivalent), including ownership of production systems. Strong programming skills in Python, plus solid data engineering foundations. Good to have experience with AI frameworks (Langraph, Strand etc), orchestration (Airflow/Kubeflow), and streaming/processing (Kafka/Spark/Ray). Proven track record building observability for AI systems (metrics/logging/traces), with automated alerting, dashboards, and SLO management. Experience designing model governance and safety guardrails (prompt/version control, red-teaming, policy checks, approvals). Demonstrated ability to drive performance/cost optimizations (profiling, batching, caching, quantization, autoscaling) in high-traffic environments. Practical familiarity with vector search/embedding pipelines (indexing strategies, consistency, reindexing, retention). Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

Responsibilities

The role involves designing and owning core platform components that power AI across Airbnb Payments, partnering with cross-functional teams to translate requirements into robust systems with clear SLAs. Responsibilities also include building tooling for faster and safer AI development and leading efforts to raise the bar on reliability and governance for production models.