Senior
Build Reddit's LLM Gateway and GenAI platform infrastructure at scale
Interview for a Senior Software Engineer role on Reddit's Machine Learning Platform team, leading development of a large-scale GenAI Platform including an LLM Gateway with unified API endpoints, rate/token limiting, and failover. Expect deep questions on RAG systems, agentic workflows with LangChain/LangGraph, and LLMOps practices at Kubernetes scale.
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What this interview tests
- LLM Gateway design (unified endpoints, rate limiting, failover)
- RAG systems (embeddings, vector search, retrieval pipelines)
- Agentic workflows with LangChain/LangGraph
- LLMOps/MLOps practices (CI/CD, versioning, evaluation, observability)
- Kubernetes and infrastructure-as-code at scale (Terraform)
- Platform thinking and cross-team enablement
Common question themes
Design an LLM Gateway with failover across multiple providers
Walk through a RAG pipeline you built and how you evaluated retrieval quality
Describe an agentic workflow you implemented with LangChain or LangGraph and a failure mode you hit
How do you operationalize LLMOps practices for a GenAI pipeline in production
How have you scaled ML infrastructure on Kubernetes with Terraform
How do you design a platform that other engineering teams can self-serve on
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