Job DescriptionResponsibilities
- Architect, design, develop, deploy, and operate production-grade AI systems powered by LLMs, agents, retrieval, and enterprise data.
- Build agentic AI systems that leverage tool use, memory, planning, orchestration, and workflow automation to solve complex business problems.
- Design and implement scalable RAG, search, retrieval, ranking, and knowledge systems across structured and unstructured data sources.
- Develop LLM-powered applications, including prompt and context engineering, tool integrations, model routing, guardrails, and workflow orchestration.
- Optimize AI systems for quality, latency, reliability, scalability, observability, and cost efficiency.
- Establish evaluation frameworks, experimentation platforms, and feedback loops to continuously improve AI system performance and user outcomes.
- Build and maintain cloud-native services, APIs, SDKs, and distributed systems that enable reliable development and operation of AI capabilities.
- Design and support asynchronous communication patterns, event-driven architectures, and workflow orchestration using messaging and streaming technologies.
- Partner closely with applied scientists, engineers, product managers, and domain experts to translate ambiguous requirements into scalable technical solutions.
- Drive architecture decisions, mentor engineers, and raise engineering standards across the organization.
ResponsibilitiesQualifications- 8+ 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.
QualificationsUS: Hiring Range in USD from: $114,600 to $234,600 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.
Career Level - IC4
