Senior Software Engineer -Payments

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 software 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).