Job description

Oracle Cloud Infrastructure’s (OCI) Developer Platform Tools and Services organization builds the next generation of developer productivity platforms, intelligent development workflows, and AI-powered engineering tools and platforms that accelerate software delivery across the enterprise. We are seeking a Senior Platform Software Engineer to design, build, and operate scalable services that improve the developer experience and increase engineering productivity. You will work across platform engineering, distributed systems, cloud-native technologies, machine learning, large language models (LLMs), and developer tooling. A key focus of this role is building a new AI-native testing platform that learns real-world service behavior, generates realistic test traffic, safely validates workloads, and detects regressions with minimal manual test authoring. Its closed-loop workflow observes changing traffic patterns, executes and evaluates tests, and continuously improves future coverage. You will help take this platform from early architecture through production deployment and enterprise-wide adoption, working with engineers, product managers, data scientists, and OCI service teams. Key Responsibilities • Design, build, deploy, and operate highly available platform services for developer productivity and AI-assisted engineering workflows. • Lead the architecture and delivery of scalable systems that analyze service behavior, model traffic patterns, generate realistic workloads, and evaluate results. • Develop agent-assisted workflows that plan, execute, and evaluate canary, functional, integration, load, and performance tests within defined safety controls. • Apply machine learning and LLM capabilities to service telemetry, API changes, incidents, test results, and engineering knowledge. • Build safe traffic-generation and workload-modeling systems that reflect production usage, service dependencies, and changing traffic patterns. • Develop evaluation and diagnostic capabilities for functional correctness, latency, error rates, reliability, scalability, and regression detection. • Provide actionable explanations of failures, including what changed, likely sources of impact, and how to reproduce an issue. • Automate the conversion of incidents, failed canaries, and detected regressions into reusable test coverage. • Design APIs, data pipelines, and integrations that make intelligent testing capabilities accessible across OCI engineering teams. • Establish strong practices for reliability, observability, security, privacy, performance, and responsible AI while mentoring engineers and influencing technical direction. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. • Four or more years of professional software engineering experience building and operating production systems. • Proficiency in one or more modern programming languages, such as Java, Go, Python, or C++. • Strong knowledge of system design, algorithms, data structures, concurrency, APIs, and scalable architectures. • Experience building backend services, distributed systems, microservices, event-driven applications, or large-scale data pipelines. • Experience developing and operating software in cloud environments using CI/CD, containerization, and cloud-native architectures. • Experience with service testing, reliability, observability, performance engineering, or production operations. • Ability to troubleshoot complex systems using logs, metrics, traces, telemetry, and production data. • Demonstrated ability to lead technical initiatives across teams, communicate architectural decisions clearly, and deliver high-quality production software. Preferred Qualifications • Experience building developer platforms, CI/CD systems, testing frameworks, or engineering productivity tools. • Experience developing or integrating production solutions using machine learning, generative AI, or LLMs. • Familiarity with AI agents, tool-using models, retrieval-augmented generation, prompt engineering, or LLM evaluation techniques. • Experience with machine learning frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or equivalent technologies. • Experience with traffic replay, workload modeling, canary analysis, load testing, performance testing, or chaos engineering. • Hands-on experience with Kubernetes, containers, service meshes, and OCI or another major public cloud. • Experience analyzing API schemas, code changes, service dependencies, incidents, and production traffic. • Experience mentoring engineers and influencing architecture across teams. Why Join Us • Shape a new AI-native developer platform from foundational architecture through production adoption. • Build systems that improve how thousands of engineers develop, test, and release software. • Solve complex, real-world problems spanning distributed systems, cloud infrastructure, machine learning, and generative AI. • Help engineering teams reduce manual testing, detect regressions earlier, diagnose failures faster, and release with greater confidence. • Work with experienced engineers, data scientists, product managers, and OCI service teams while expanding your technical influence and expertise. #LI-SP1 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: $92,500 to $209,500 per annum. May be eligible for bonus and equity. 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. Career Level - IC3 Design and build an AI-native testing platform that learns service behavior and generates functional, integration, canary, and load tests. They will develop traffic-generation, test-execution, evaluation, and regression-diagnosis capabilities and integrate them with CI/CD workflows. They will also implement safety controls, observability, and continuous-learning mechanisms to improve test coverage and release confidence.

Requirements

Must-haves

Design, build, deploy, and operate highly available platform services for developer productivity and AI-assisted engineering workflows.
Lead the architecture and delivery of scalable systems that analyze service behavior, model traffic patterns, generate realistic workloads, and evaluate results.
Develop agent-assisted workflows that plan, execute, and evaluate canary, functional, integration, load, and performance tests within defined safety controls.
Apply machine learning and LLM capabilities to service telemetry, API changes, incidents, test results, and engineering knowledge.
Build safe traffic-generation and workload-modeling systems that reflect production usage, service dependencies, and changing traffic patterns.
Develop evaluation and diagnostic capabilities for functional correctness, latency, error rates, reliability, scalability, and regression detection.
Provide actionable explanations of failures, including what changed, likely sources of impact, and how to reproduce an issue.
Automate the conversion of incidents, failed canaries, and detected regressions into reusable test coverage.
Design APIs, data pipelines, and integrations that make intelligent testing capabilities accessible across OCI engineering teams.
Establish strong practices for reliability, observability, security, privacy, performance, and responsible AI while mentoring engineers and influencing technical direction.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Four or more years of professional software engineering experience building and operating production systems.
Proficiency in one or more modern programming languages, such as Java, Go, Python, or C++.
Strong knowledge of system design, algorithms, data structures, concurrency, APIs, and scalable architectures.
Experience building backend services, distributed systems, microservices, event-driven applications, or large-scale data pipelines.
Experience developing and operating software in cloud environments using CI/CD, containerization, and cloud-native architectures.

Nice-to-haves

Experience building developer platforms, CI/CD systems, testing frameworks, or engineering productivity tools.
Experience developing or integrating production solutions using machine learning, generative AI, or LLMs.
Familiarity with AI agents, tool-using models, retrieval-augmented generation, prompt engineering, or LLM evaluation techniques.
Experience with machine learning frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or equivalent technologies.
Experience with traffic replay, workload modeling, canary analysis, load testing, performance testing, or chaos engineering.
Hands-on experience with Kubernetes, containers, service meshes, and OCI or another major public cloud.
Experience analyzing API schemas, code changes, service dependencies, incidents, and production traffic.
Experience mentoring engineers and influencing architecture across teams.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmapijavagopythonci/cdkubernetes

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave