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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # REMOTE -Principal Software Developer- Agentic AI,... - **Company:** Oracle - **Location:** Concord, NH, United States - **Experience:** Expert - **Salary:** $114,600.0 - $234,600.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Data Structures, Software Debugging, Distributed Systems, Elasticsearch, Python (Programming Language), Knowledge-Based Systems, Machine Learning, Queueing Systems, Software Engineering, Data Streaming, Workflow Management Systems, Chatbots, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Concurrency, Apache Spark, Backend, Event Driven Architecture, Containerization, Kubernetes, Information Technology, Low Latency, Apache Kafka, Video Streaming, Virtual Agents, Asynchronous Programming, Oracle Cloud Infrastructure, Serverless Computing, Docker - **Published:** July 4, 2026 - **Apply:** https://www.juju.com/job/00000000gdv33g ## About the Role + 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. ## Description + 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. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Agentic AI Systems for Critical Workloads](https://www.wearedevelopers.com/videos/1592-agentic-ai-systems-for-critical-workloads) - [Beyond Chatbots: How to build Agentic AI systems](https://www.wearedevelopers.com/videos/1629-beyond-chatbots-how-to-build-agentic-ai-systems) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Got AI ideas but no money? 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