Senior AI Data & State Infrastructure Engineer

EY; Akron (OH); Hybrid; USD 107,000 - 177,000; Full time

Job summary

EY seeks an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform, including data stores, memory tiers, and event streaming across cloud, on-prem, edge, and air-gapped environments. You’ll manage relational, vector, and graph stores, ensure durability, and drive cross-environment data workflows.

Responsibilities include owning Kafka/NATS/CDC pipelines, ensuring schema evolution, and multi-tenant isolation while enabling reliable data services for regulator-ready client

Qualifications

• Production databases handling at scale with HA
• Streaming architectures and event-driven design
• Durability, recoverability, and data correctness in regulated contexts
• Operators/Kubernetes and storage across multi-env clouds
• Schema governance across producers/consumers
• Clear ownership and data contracts across teams
• Automation and IaC for data systems

Responsibilities

• Own memory and data stores across environments (PostgreSQL, Redis, vector stores, graph stores)
• Own streaming and async messaging (Kafka, NATS, Debezium)
• Ensure data durability and recoverability (backup, PITR)
• Build and operate streaming/CDC pipelines with schema governance
• Maintain multi-tenant isolation and portable state across environments
• Provide data and lineage substrate for governance and AI capabilities

Skills

Production databases

Streaming architectures

Data durability

Kubernetes

Multi-tenant isolation

Schema governance

Communication

Automation IAAC

Education

Bachelor’s or Master’s in Computer Science

Tools

PostgreSQL

Redis/Valkey

Qdrant/Milvus/PGVector

Neo4j

MinIO/OpenEBS

Kafka/Strimzi

Debezium

Apache Flink

CloudEvents/Schema registry

Job description

EY seeks an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform, including data stores, memory tiers, and event streaming across cloud, on-prem, edge, and air-gapped environments. You’ll manage relational, vector, and graph stores, ensure durability, and drive cross-environment data workflows.

Responsibilities include owning Kafka/NATS/CDC pipelines, ensuring schema evolution, and multi-tenant isolation while enabling reliable data services for regulator-ready client