Senior AI Systems Engineer – Stateful Data & Streaming

EY; San Diego (CA); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Paid time off

Job summary

EY seeks an AI Systems Engineer to own the stateful backbone of its AI-native platform, spanning relational, vector, and object stores across cloud, on-prem, edge, and air-gapped environments. You will manage durable workflows, streaming and change data capture pipelines, and ensure reliable, consistent data for agentic AI workloads.

You’ll work within a hybrid EY model, shaping scalable data infrastructure, and collaborating with platform, trust, runtime, and delivery teams to minimize toil and

Qualifications

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

Responsibilities

• Own memory and data stores across environments and tenants.
• Own event streaming and async messaging pipelines.
• Ensure data durability, consistency and recoverability across systems.
• Build and operate streaming and CDC pipelines with schema governance.
• Make state multi-tenant and portable across cloud and on-prem.
• Provide data and lineage substrate for governance and observability.

Skills

Production databases

Streaming architectures

Reliability and durability

Multi-environment operation

Data governance

Communication

Automation and IaC

Education

Bachelor’s or Master’s degree in CS or related field

Tools

PostgreSQL

Redis/Valkey

Qdrant

Milvus

PGVector

Neo4j

MinIO/OpenEBS

Apache Kafka

Strimzi

NATS

Debezium

Flink

CloudEvents

Job description

EY seeks an AI Systems Engineer to own the stateful backbone of its AI-native platform, spanning relational, vector, and object stores across cloud, on-prem, edge, and air-gapped environments. You will manage durable workflows, streaming and change data capture pipelines, and ensure reliable, consistent data for agentic AI workloads.

You’ll work within a hybrid EY model, shaping scalable data infrastructure, and collaborating with platform, trust, runtime, and delivery teams to minimize toil and