Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AWS @ 3
Audit @ 3
Azure @ 3
Compliance @ 3
Data Engineering @ 6
Data Modeling @ 6
Data Pipelines @ 6
Databricks @ 3
GCP @ 3
GitHub @ 3
Observability @ 6
Python @ 5
Reporting @ 6
SQL @ 5
Salesforce @ 3
Security @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. The team supports identity, access, infrastructure security, enterprise systems, and internal productivity.
This role focuses on building the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. You will design and maintain pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and audit teams to turn complex system behavior into reliable control data products.
Responsibilities
- Build reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data.
- Create data quality, lineage, reconciliation, and completeness checks for SOX and other audit use cases.
- Design automated evidence-generation workflows that produce complete, accurate, and repeatable audit populations, exports, dashboards, and control artifacts.
- Develop control-monitoring logic to detect drift, missing evidence, stale access, direct system changes, overdue activity, and other control exceptions.
- Partner with Security, IT, Infrastructure, Engineering, Risk Management, and system owners to understand source systems, validate data, and improve automation reliability.
- Translate technical system behavior, data flows, access models, and validation results into clear explanations for auditors, control owners, and technical stakeholders.
Requirements
- Strong data engineering, analytics engineering, or software/data systems experience, including building reliable datasets, pipelines, queries, dashboards, or automated reporting workflows.
- Hands-on SQL experience and proficiency with at least one scripting or programming language, such as Python.
- Experience working with enterprise system data, including identity platforms, HR systems, ticketing systems, cloud environments, source control systems, SaaS applications, or audit and compliance tooling.
- Strong understanding of data modeling, lineage, completeness, accuracy, reconciliation, validation, observability, and repeatability.
- Ability to reason through messy source-system data, inconsistent identifiers, nested groups, stale records, missing owners, direct assignments, and downstream application drift.
- Experience supporting security, IT controls, SOX, audit readiness, risk, compliance, or regulated technology environments.
- Ability to explain technical systems, data flows, and control logic clearly to engineering and audit stakeholders.
- Strong ownership, judgment, and attention to detail in high-stakes, time-sensitive environments.
Nice to Have
- Experience with Entra ID, Workday, GitHub, Databricks, Salesforce, or similar platforms.
- Experience with cloud infrastructure environments such as Azure, AWS, or GCP.
Working Style
- Enjoy turning messy operational processes into clean, repeatable systems.
- Comfortable working at the intersection of data, controls, engineering, and audit.
- Able to work deeply technically while explaining work clearly to auditors and executives.
- Strong focus on evidence quality, data integrity, and defensible documentation.
- Energized by building automation that reduces manual effort and improves control reliability.
- Able to partner with engineers while maintaining a strong control standard.
Benefits
- Base salary range of $293,000–$385,000 USD, plus equity.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health and dependent care expenses, as well as commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental leave, medical leave, and caregiver leave.
- Paid time off, company holidays, office closures, and paid sick or safe time.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional benefits may include charitable donation matching and wellness stipends.
OpenAI is an equal opportunity employer and is committed to providing reasonable accommodations to applicants with disabilities. Background checks are administered in accordance with applicable law.