Senior AI Data Platform Engineer

EY

Las Vegas (NV)

Hybrid

USD 107,000 - 177,000

Full time

4 days ago
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Benefits offered by this job

Hybrid work model
Medical and dental coverage
Pension and 401(k)
Paid time off
Flexible vacation policy

Job summary

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.

Responsibilities

  • 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.

Skills

Database administration
Streaming architectures
Durability mindset
Cross-environment operation
Schema governance
Communication
Infrastructure as code

Education

Bachelor’s or Master’s degree in Computer Science

Tools

PostgreSQL
Redis
Qdrant
Milvus
PGVector
Neo4j
MinIO
OpenEBS
Apache Kafka
NATS
Debezium
Apache Flink
CloudEvents
Schema registry

Job description

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.

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