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oracle

Lead Principal Platform Software Engineer

Oracle
USA
Full-time
Lead · 12+ years experience
Onsite
Discovered 2 days ago
awsazuredockerelasticsearchgcpjava

Full Job Posting

Qualifications

  • 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: Medical, dental, and vision insurance, including expert medical opinion Short term disability and long term disability Life insurance and AD&D Supplemental life insurance (Employee/Spouse/Child) Health care and dependent care Flexible Spending Accounts Pre-tax commuter and parking benefits 401(k) Savings and Investment Plan with company match 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. 11 paid holidays 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. Paid parental leave Adoption assistance Employee Stock Purchase Plan Financial planning and group legal 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.
  • 12+ years of professional experience in software engineering, machine learning engineering, applied machine learning, or related fields.
  • BS/MS/PhD in Computer Science, Engineering, Machine Learning, Artificial Intelligence, or equivalent practical experience.
  • Proven track record of designing, building, and operating production ML, AI, LLM, RAG, search, recommendation, conversational AI, or agentic AI systems at scale.
  • Strong software engineering fundamentals, including distributed systems, concurrency, APIs, data structures, algorithms, testing, debugging, and production operations.
  • Proficiency in Python and Java with experience developing and maintaining production software in both languages.
  • Hands-on experience building scalable backend services, cloud-native systems, APIs, distributed applications, or model-serving platforms.
  • Experience with modern LLM ecosystems, including prompt engineering, tool calling, retrieval-augmented generation, model serving, evaluation, and deployment.
  • Experience building search, retrieval, ranking, vector database, or enterprise knowledge systems.
  • Experience with asynchronous communication patterns, message queues, pub/sub systems, data streaming platforms, or event-driven architectures.
  • Experience with containerized applications and Kubernetes-based deployments.
  • Strong technical judgment and the ability to balance quality, latency, reliability, scalability, and cost tradeoffs.
  • Demonstrated ownership of complex technical problems from architecture through production operation.
  • Strong communication skills and experience working effectively across engineering, product, and applied science teams.

Preferred Qualifications

  • Experience building agentic AI systems involving planning, tool orchestration, memory, autonomous workflows, or multi-agent architectures.
  • Experience with frameworks and platforms such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, MCP, or equivalent orchestration technologies.
  • Experience with retrieval and ranking technologies such as Elasticsearch, OpenSearch, vector databases, hybrid search, reranking, and query understanding systems.
  • Experience designing and operating production LLM serving platforms with responsibility for latency, throughput, reliability, scalability, observability, and cost efficiency.
  • Experience with model adaptation techniques such as fine-tuning, LoRA, distillation, preference optimization, or domain adaptation.
  • Experience building evaluation systems, A/B testing frameworks, human-in-the-loop review processes, and AI quality measurement platforms.
  • Experience with OCI, AWS, Azure, or GCP and technologies such as Docker, Kubernetes, Kafka, Spark, or equivalent distributed systems.
  • Experience developing tools, frameworks, APIs, or platforms used by applied scientists, data scientists, or machine learning engineers.
  • Experience building AI systems in healthcare, enterprise SaaS, regulated environments, or other privacy-sensitive domains.
  • Demonstrated technical leadership through architecture ownership, mentoring, cross-functional collaboration, and delivery of high-impact initiatives.

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