Backend / Platform Engineer, AI Analytic Engines
Core
Architect and build scalable, low-latency backend services and evaluation engines for real-time AI safety monitoring, compliance, and runtime intervention in distributed pipelines.
Role type
Senior Backend/Platform Engineer (AI Safety & Observability)
Builds
Real-time evaluation engines, runtime intervention layers, and vector database pipelines for AI control systems.
Domain
Enterprise AI safety, LLM observability, and distributed systems engineering.
Required skills
Python, Go, streaming data pipelines (Kafka, Pulsar, Redis Streams), high-QPS low-latency service design, vector databases (FAISS, Weaviate, Qdrant, pgvector), cloud-native infrastructure (Kubernetes, serverless), OpenTelemetry, build vs buy trade-offs
Preferred skills
gRPC, FastAPI, asyncio, ClickHouse, Apache Arrow, agent frameworks (LangChain, CrewAI, AutoGen), trust & safety compliance, secure enterprise integrations
Technologies
Kafka, Pulsar, Redis Streams, Kubernetes, gRPC, FastAPI, OpenTelemetry, FAISS, Weaviate, Qdrant, pgvector, ClickHouse, Apache Arrow
Responsibilities
Architect scalable services for real-time and batch AI evaluations; design core evaluation engines using heuristics and foundation models; build runtime intervention layers for enforcement actions; create frameworks for pluggable evaluators and automated deployment; configure vector database pipelines for RAG use cases; implement reliability controls like micro-batching and back-pressure.
Seniority
Senior, hands-on IC
