DataVisor, the world’s leading AI-powered Fraud and Risk Platform, is seeking an AI Engineer to serve as a technical architect for our Intelligence Layer and Data Consortium. This specialized engineering role focuses on building high-scale production services and data pipelines that ingest real-time signals from millions of users and enable our Agentic Flow to auto-tune strategies. You will design, build, and operate distributed, production-grade systems and data pipelines; own and evolve the internal AI agent workflow and tooling; and help migrate it to a new production-grade agent framework. You will also develop AI applications and agentic flows using state-of-the-art large language models (LLMs), collaborating with Data Science and Solutions teams to integrate traditional ML models, rule engines, and label pipelines into production. This role is primarily a production software engineering role; classic ML modeling is a plus but not required.

Primary Responsibilities: - Consortium Data Engineering: Architect and maintain high-throughput data pipelines (Spark, Kafka, or Flink) to ingest, process, and aggregate real-time signals (such as device fingerprints and behavioral biometrics) into our central intelligence graph. - High-Scale System Design: Design distributed systems to support our global data network, ensuring the platform can handle 10,000+ transactions per second with P99 latency under 150 ms. - Agentic Flow & AI Application Development: Build agentic flows and AI applications by leveraging state-of-the-art, out-of-the-box LLMs (e.g., OpenAI, Anthropic, Google)

DataVisor, the world’s leading AI-powered Fraud and Risk Platform, is seeking an AI Engineer to serve as a technical architect for our Intelligence Layer and Data Consortium. This specialized engineering role focuses on building high-scale production services and data pipelines that ingest real-time signals from millions of users and enable our Agentic Flow to auto-tune strategies. You will design, build, and operate distributed, production-grade systems and data pipelines; own and evolve the internal AI agent workflow and tooling; and help migrate it to a new production-grade agent framework. You will also develop AI applications and agentic flows using state-of-the-art large language models (LLMs), collaborating with Data Science and Solutions teams to integrate traditional ML models, rule engines, and label pipelines into production. This role is primarily a production software engineering role; classic ML modeling is a plus but not required.

Primary Responsibilities: - Consortium Data Engineering: Architect and maintain high-throughput data pipelines (Spark, Kafka, or Flink) to ingest, process, and aggregate real-time signals (such as device fingerprints and behavioral biometrics) into our central intelligence graph. - High-Scale System Design: Design distributed systems to support our global data network, ensuring the platform can handle 10,000+ transactions per second with P99 latency under 150 ms. - Agentic Flow & AI Application Development: Build agentic flows and AI applications by leveraging state-of-the-art, out-of-the-box LLMs (e.g., OpenAI, Anthropic, Google)