Remote Principal Software Developer- Agentic AI

Position: [Remote] Principal Software Developer- Agentic AI
** Job Description*
* Building off our Cloud momentum, Oracle has formed a new organization - Oracle Health & AI. This team will focus on product development and product strategy for Oracle Health, while building out a complete platform supporting modernized, automated healthcare. This is a net new line of business, constructed with an entrepreneurial spirit that promotes an energetic and creative environment. We are unencumbered and will need your contribution to make it a world class engineering center with the focus on excellence.

** Responsibilities*
* ** Responsibilities*
* + 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.

** Qualifications*
* + 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.

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Experience with asynchronous communication patterns, message queues, pub/sub systems, data streaming platforms, or event-driven architectures.

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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 Lang Graph, Lang Chain, Llama Index, Semantic Kernel, MCP, or equivalent orchestration technologies.

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Experience with retrieval and ranking technologies such as Elasticsearch, Open Search, 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.

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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…