AI Systems Engineer: Stateful Data & Streaming Lead

EY; New York (NY); On-site; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking an AI Systems Engineer to own the stateful backbone of EY's AI-native platform, spanning relational and vector stores, streaming pipelines, and durable workflows across cloud, on-prem, edge, and air-gapped environments.

You will ensure data durability and recoverability, lead multi-tenant isolation, and collaborate with platform and governance teams to enable reliable, compliant AI workloads with scalable data infrastructure.

Qualifications

• Eight+ years operating production data infrastructure or streaming systems.
• Experience with relational databases (PostgreSQL) and caching ( Redis/Valkey ).
• Hands-on with vector/graph databases (Qdrant, Milvus, PGVector, Neo4j).
• Strong knowledge of Kafka, NATS, Debezium, and stream processing.

Responsibilities

• Own memory and data stores across environments including PostgreSQL and vector stores.
• Manage event streaming and async messaging with Kafka and NATS JetStream.
• Ensure data durability, consistency, and recoverability with backups and PITR.
• Build streaming and CDC pipelines with schema governance.
• Make state multi-tenant with isolation and consistent semantics.
• Provide data lineage and governance substrate for AI capabilities.

Skills

Data infrastructure at scale

Streaming architectures

Durability and recoverability

Cross-environment operations

Schema governance

Communication skills

Infrastructure as code

Education

Bachelor’s or Master’s in CS or related

Tools

PostgreSQL

Redis/Valkey

Qdrant

Milvus

PGVector

Neo4j

Kafka

NATS

Debezium

Flink

MinIO

OpenEBS

Job description

EY is seeking an AI Systems Engineer to own the stateful backbone of EY's AI-native platform, spanning relational and vector stores, streaming pipelines, and durable workflows across cloud, on-prem, edge, and air-gapped environments.

You will ensure data durability and recoverability, lead multi-tenant isolation, and collaborate with platform and governance teams to enable reliable, compliant AI workloads with scalable data infrastructure.