Senior AI Data Platform Engineer

EY; Las Vegas (NV); Hybride; USD 107 000 - 177 000; Plein temps

Avantages offerts par ce poste

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Flexible vacation policy

Résumé du poste

EY is seeking an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform, spanning relational, vector, graph, and object stores, with durable, scalable access across cloud and isolated environments. The role emphasizes data durability, cross-environment consistency, and governance for AI workloads.

You will own event streaming, change data capture, and schema evolution, ensuring reliable pipelines and multi-tenant isolation.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.

Responsabilités

• Own memory and data stores across environments (relational, vector, graph, object storage).
• Own streaming and async messaging (Kafka, NATS, Debezium).
• Ensure data durability, consistency, and recoverability across clouds, on-prem, edge, and air-gapped environments.
• Build and operate streaming and CDC pipelines with schema governance.
• Make state multi-tenant and portable with isolation and performance.
• Provide data and lineage substrate for governance and AI capabilities.

Connaissances

Database administration

Streaming architectures

Durability mindset

Cross-environment operation

Schema governance

Communication

Infrastructure as code

Formation

Bachelor’s or Master’s degree in Computer Science

Outils

PostgreSQL

Redis

Qdrant

Milvus

PGVector

Neo4j

MinIO

OpenEBS

Apache Kafka

NATS

Debezium

Apache Flink

CloudEvents

Schema registry

Description du poste

EY is seeking an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform, spanning relational, vector, graph, and object stores, with durable, scalable access across cloud and isolated environments. The role emphasizes data durability, cross-environment consistency, and governance for AI workloads.

You will own event streaming, change data capture, and schema evolution, ensuring reliable pipelines and multi-tenant isolation.