14 days ago
Base Salary
$114k - $306k/yr
Responsibilities
- Architect, design, develop, deploy, and operate production-grade AI systems powered by LLMs, agents, retrieval, and enterprise data.
- Build agentic AI systems using tool use, memory, planning, orchestration, and workflow automation.
- Design scalable RAG, search, retrieval, ranking, and knowledge systems across structured and unstructured data.
- Develop LLM-powered applications with 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 improve AI system performance and user outcomes.
- Build cloud-native services, APIs, SDKs, and distributed systems supporting reliable AI development and operations.
- Design asynchronous, event-driven, messaging, streaming, and workflow orchestration patterns.
- Partner with engineering, product, applied science, and domain teams to turn ambiguous requirements into scalable solutions.
- Drive architecture decisions, mentor engineers, and raise engineering standards.
Requirements
- 12+ years of professional experience in software engineering, machine learning engineering, applied machine learning, or related fields.
- Bachelor’s, master’s, or doctoral degree in computer science, engineering, machine learning, artificial intelligence, or equivalent practical experience.
- Production experience designing, building, and operating ML, AI, LLM, RAG, search, recommendation, conversational AI, or agentic AI systems at scale.
- Strong fundamentals in distributed systems, concurrency, APIs, data structures, algorithms, testing, debugging, and production operations.
- Proficiency developing and maintaining production software in both Python and Java.
- Experience building scalable backend services, cloud-native systems, APIs, distributed applications, or model-serving platforms.
- Experience with prompt engineering, tool calling, retrieval-augmented generation, model serving, evaluation, and deployment.
- Experience with search, retrieval, ranking, vector database, or enterprise knowledge systems.
- Experience with asynchronous communication, message queues, pub/sub systems, data streaming, or event-driven architectures.
- Experience with containerized applications and Kubernetes-based deployments.
- Ability to balance quality, latency, reliability, scalability, and cost tradeoffs and own complex technical problems through production operation.
- Strong communication and cross-functional collaboration skills.
- Preferred experience with agentic AI, LangGraph, LangChain, LlamaIndex, Semantic Kernel, MCP, Elasticsearch, OpenSearch, vector databases, hybrid search, reranking, and query understanding.
- Preferred experience operating LLM serving platforms, applying fine-tuning or other model adaptation techniques, and building evaluation or human-in-the-loop quality systems.
- Preferred experience with OCI, AWS, Azure, GCP, Docker, Kubernetes, Kafka, Spark, AI platforms, developer tools, healthcare, enterprise SaaS, regulated, or privacy-sensitive environments.
- Preferred demonstrated technical leadership through architecture ownership, mentoring, cross-functional collaboration, and delivery of high-impact initiatives.
Benefits
- US hiring range is $113,600 to $306,400 per annum, with potential bonus, equity, and compensation deferral.
- Medical, dental, vision, disability, life, and AD&D insurance are offered.
- Benefits include flexible spending accounts, pre-tax commuter and parking benefits, a 401(k) plan with company match, paid vacation, 11 paid holidays, paid sick leave, and paid parental leave.
- Additional benefits include adoption assistance, an employee stock purchase plan, financial planning, group legal services, and voluntary auto, homeowner, and pet insurance.
- US-based employees must complete identity verification involving collection and processing of biometric information, subject to legally permitted accommodations.
Tech Stack
Categories
About Oracle
Oracle builds database technology, enterprise applications, and Oracle Cloud Infrastructure for companies and governments. Its business spans cloud subscriptions, software licenses, and support services across ERP, HCM, CX, and industry suites, plus NetSuite. Founded in 1977 and headquartered in Austin, Texas, Oracle is a public company traded on the NYSE and serves global customers migrating and running critical workloads in its cloud.