Lead Principal Platform Software Engineer

Oracle AI Data Platform (AIDP) is a unified, enterprise-grade cloud service that brings together data management, governance, analytics, and generative AI development into a single platform. AIDP team is seeking an experienced Lead Principal Software Engineer to lead key initiatives that accelerate development and adoption of data platform capabilities. 

In this role, you will drive the design, development, and integration of state-of-the-art technologies for data engineering that enable large scale AI enabled enterprise. You will provide technical leadership for our data connectivity frameworks and implement functionality such as zero-copy, Zero-ETL and data ingestion. You will architect and scale our enterprise data lineage functionality, using extensible open standards. You will build scalable, performant and secure frameworks to map end-to-end data flows - ensuring column-level visibility from source ingestion to downstream analytics.

You will collaborate with stakeholders across product, engineering, support and operations to influence the AI Data Platform’s roadmap and deliver differentiated value to enterprise customers and partners. You should be able to function well in a large geographically distributed team and have the hunger to drive for impactful results on a fast-paced environment.

Disclaimer:

Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $113,600 to $306,400 per annum. May be eligible for bonus, equity, and compensation deferral.


Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.
Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following:
1. Medical, dental, and vision insurance, including expert medical opinion
2. Short term disability and long term disability
3. Life insurance and AD&D
4. Supplemental life insurance (Employee/Spouse/Child)
5. Health care and dependent care Flexible Spending Accounts
6. Pre-tax commuter and parking benefits
7. 401(k) Savings and Investment Plan with company match
8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.
9. 11 paid holidays
10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
11. Paid parental leave
12. Adoption assistance
13. Employee Stock Purchase Plan
14. Financial planning and group legal
15. Voluntary benefits including auto, homeowner and pet insurance

The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.
As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment.

Required skills and experience

• Demonstrated technical leadership and architectural experience setting direction for complex systems, resolving ambiguous requirements, and driving initiatives across multiple engineering teams. Ability to balance scalability, reliability, security, performance, and delivery priorities.

• Strong hands-on software engineering experience with backend language such as Java or Python, with strong knowledge of API design, data modeling, and automated testing. Ability to diagnose complex failures across service and infrastructure boundaries.

• Strong understanding of concurrency, asynchronous processing, consistency, state management, retries, timeouts, idempotency, back-pressure, and recovery from partial failures, applied to large-scale or multi-tenant platform services.

• Data and integration experiencebuilding pipelines, connectors, or data platform components that integrate with heterogeneous external systems, including managing schema evolution and API and data contracts.

• Demonstrated hands-on use of Claude Code and/or Codex to deliver production software, including repository exploration, implementation planning, code generation, refactoring, debugging, test development, and code review. 

• Ability to independently assess AI-generated designs, code, and tests; identify incorrect assumptions and missing coverage; and validate correctness, security, performance, and maintainability. Retains deep understanding and accountability for all delivered software.

• Experience owning services from design through deployment and operations, including observability, service-level objectives, incident response, root-cause analysis, capacity planning, and durable corrective actions.

• Ability to communicate trade-offs to engineering and product leaders, mentor senior engineers, and build reusable tools and practices that improve quality and delivery across teams.

Preferred skills and experience

• Experience with data platform technologies such as Apache Spark, SQL processing engines, notebooks, or lakehouse architectures.

• Experience with orchestration or messaging platforms such as Apache Airflow, Temporal, Argo Workflows, Kafka, or comparable systems.

• Familiarity with OCI or other major cloud platforms, Kubernetes, infrastructure as code, CI/CD, and cloud identity and authorization.

• Experience designing extensible, connector-based architectures, with API versioning and backward compatibility for platform services used by many teams.

• Evidence of measurable engineering improvements through AI-assisted development, reusable agent workflows, and automated validation.