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About the Role

We are seeking an AI Systems Engineer to own the stateful backbone of EY’s AI-native platform, including the data stores, memory tiers, and event streaming systems. This role ensures that agentic AI workloads have durable, performant, and consistent access to data across various environments. It is ideal for a data-infrastructure engineer comfortable operating production databases and high-throughput streaming systems, who understands that state is the hardest part of any distributed platform to get right.

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/block storage (MinIO, OpenEBS Mayastor), across every environment and tenant.
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 (schema and event contracts).
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.

Requirements

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.

Skills

Deep expertise operating production databases and data stores at scale, including relational, key-value, vector, graph, and object storage.
Strong command of streaming and event-driven architectures (Kafka, NATS, CDC, stream processing) and the consistency tradeoffs they involve.
A durability-first mindset: thinking in terms of consistency, recoverability, blast radius, and data correctness under failure.
Ability to operate stateful systems consistently across managed cloud and self-hosted OSS in cloud, on-prem, edge, and air-gapped environments.
Strong grasp of schema governance and evolution, preventing breaking changes across producers and consumers.
Strong communicator able to guide consuming teams toward the right storage and streaming patterns.
Orientation toward reliability and toil reduction through automation and infrastructure-as-code for data systems.
Experience with durable workflow engines (DBOS, Temporal, or equivalents).
Experience with data lineage and metadata tooling (OpenLineage, Marquez, or equivalents).
Proven track record operating data systems under compliance, security, or regulatory constraints, including data-at-rest and in-transit protection.
Familiarity with multi-tenant data isolation and per-tenant performance management.
Experience with cross-environment replication and DR strategies tiered by RPO/RTO (e.g., MirrorMaker, CloudNativePG PITR).
Exposure to regulated delivery environments (financial services, tax, healthcare, risk).

Location

Anywhere in Country

Work Type

Hybrid

Experience Level

8+ years operating production data infrastructure, streaming systems, or database platforms at scale.

Education Level

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

Salary/Compensations

US base salary range: $106,900 to $176,500
New York City Metro Area, Washington State and California (excluding Sacramento) base salary range: $128,400 to $200,600

Benefits

Comprehensive compensation and benefits package
Medical and dental coverage
Pension and 401(k) plans
Wide range of paid time off options
Flexible vacation policy
Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence

About the Company

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions.
Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Equal Opportunity

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities.