Senior Stateful AI Data Systems Engineer

EY; San Jose (CA); Hybrid; USD 128,000 - 201,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

401(k)/Pension plans

Job summary

EY is seeking an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. You’ll manage relational, vector, and graph stores, durable workflows, and streaming pipelines for reliable, multi-tenant data systems.

A durability-first mindset and experience with Kubernetes are essential. You’ll work in EY’s hybrid model, balancing production data workloads with governance and automation to reduce toil and improve data trust

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years operating production data infrastructure, streaming systems, or database platforms at scale.
• Hands‑on expertise with relational databases (PostgreSQL) and caching (Redis/Valkey), including HA, replication, and backup/recovery.
• Exposure to AI/ML data patterns — embeddings, retrieval, feature/state stores for agentic workloads.
• Production experience with vector and/or graph databases (Qdrant, Milvus, PGVector, Neo4j) in AI/ML contexts.
• Deep experience with event streaming and messaging (Apache Kafka/Strimzi, NATS) and change data capture (Debezium).
• Experience with stream processing (Apache Flink) and event/schema governance (CloudEvents, schema registry).
• Experience running stateful systems on Kubernetes (operators, persistent volumes, object/block storage such as MinIO/OpenEBS).
• Ability to define clean ownership boundaries and data/schema contracts with platform, trust, runtime, and delivery teams.

Responsibilities

• Own the memory and data stores: relational and durable state (PostgreSQL, DBOS durable workflows), caching (Redis/Valkey), vector stores (Qdrant/Milvus/PGVector), knowledge graphs (Neo4j), and object/storage across environments.
• Own event streaming and async messaging: Apache Kafka (Strimzi), NATS JetStream (agent-to-agent), Debezium (change data capture), Apache Flink (stream processing), and Apicurio/CloudEvents.
• Own data durability, consistency, and recoverability: replication, backup/restore, point-in-time recovery, and cross-environment data movement, tiered by RPO/RTO.
• Build and operate streaming and CDC pipelines that move data reliably between stores and services, with schema governance and evolution that prevents breaking changes across producers and consumers.
• Make state multi-tenant and portable, ensuring isolation, performance, and consistent semantics whether running on managed cloud services or self-hosted OSS in an air-gapped environment.
• Provide the data and lineage substrate that downstream governance, observability, and AI knowledge capabilities depend on, as well as integrating with lineage tooling.

Skills

Relational databases

Streaming systems

Kubernetes

Data durability

Multi-tenant architectures

Schema governance

Cloud and on‑prem

Communication skills

Education

Bachelor’s or Master’s degree in Computer Science

Tools

PostgreSQL

Redis

Valkey

Qdrant

Milvus

PGVector

Neo4j

MinIO

OpenEBS

Job description

EY is seeking an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. You’ll manage relational, vector, and graph stores, durable workflows, and streaming pipelines for reliable, multi-tenant data systems.

A durability-first mindset and experience with Kubernetes are essential. You’ll work in EY’s hybrid model, balancing production data workloads with governance and automation to reduce toil and improve data trust