LOCATION: REDWOOD SHORES OR PLEASANTON, CA ONLY

As a Senior Applications Engineer, you should be proficient in writing performant code in Java, building Agentic solutions, building distributed systems, containerization, and cloud-native architectures. You will collaborate with cross-functional teams to build scalable, reliable, and production-ready solutions. Oracle is leading development of Agentic solutions, having a good understanding and experience in leveraging the capabilities of Large Language Models would is a must have.

In this role, you will design, develop, and build scalable services that leverage from latest and greatest advancements in software development and GenAI to solve complex business problems intelligently. Your expertise will be pivotal in building end to end software solutions flows that includes data base design, conversational AI solutions, Agentic flows using LLM and other cutting-edge machine learning techniques to shape up and enhance users\' experience. You will also partner with product managers, software engineers, and operation teams to leverage engineering innovations to simplify the business requirements into scalable solutions.

The ideal candidate is highly technical, proficient in Java, data base designs and have experience of building scalable solutions, can lead across the full stack, along with good product sense and business understanding, to map the technology choices to the context of each initiative.

• Java & Microservices Architecture: Strong experience building Java-based microservices using frameworks such as Spring Boot or Helidon, with expertise in RESTful API design, containerization (Docker/Kubernetes), and distributed systems patterns.
• LLM Integration & Agentic Workflows: Hands-on experience integrating LLM APIs and designing agent-based architectures, including tool and function calling, multi-step reasoning workflows, and state management for orchestrating AI agents.
• RAG Pipeline Development: Proven ability to build retrieval-augmented generation (RAG) solutions, including embedding generation, vector databases, semantic and hybrid search, and effective document chunking strategies.
• AI Guardrails, Trust & Safety: Experience implementing safeguards such as input and output validation, PII detection and redaction, prompt injection prevention, rate limiting, content moderation, and hallucination mitigation.
• Vector Search & Databases: Proficiency with vector databases (eg, Oracle AI Vector Search, Pinecone, or similar), embedding optimization, semantic similarity search, and relational databases such as Oracle or PostgreSQL.
• Backend & API Development: Strong Back End development skills, including API authentication and authorization (OAuth 2.0, JWT), request validation, error handling, documentation, and enterprise integration patterns like event-driven and message-based architectures.
• Document Processing & Ingestion: Experience extracting and processing content from multiple formats (PDF, DOCX, PPT), including document parsing, metadata extraction, and preparing structured and unstructured data for AI pipelines.
• Cloud & DevOps: Familiarity with cloud platforms (OCI preferred; AWS, Azure, or GCP acceptable), CI/CD pipelines, automated testing, infrastructure as code, and monitoring, logging, and observability practices.
• Testing & Quality Engineering: Strong testing discipline across traditional and AI-powered systems, including unit and integration testing, prompt and output validation, performance testing, and adherence to code quality standards.
• Communication & Problem Solving: Ability to clearly explain complex AI concepts, collaborate across technical and non-technical teams, troubleshoot distributed systems, and creatively solve GenAI-specific challenges such as context management, reliability, and performance optimization.

Disclaimer: Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates. Range and benefit information provided in this posting are specific to the stated locations only.

US: Hiring Range in USD from: $79,200 to $178,100 per annum. May be eligible for bonus and equity. 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: Medical, dental, and vision insurance; 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; Paid holidays; Paid sick leave; 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.

Career Level - IC3

• Write elegant and performant code in Java.
• Create detailed technical designs specifications, present it to the team and write code as per the design.
• Stay abreast of GenAI advancements and proactively adopt new designs and patterns that deliver better solutions for the project.
• Perform thorough code reviews for the Java code written by peers.
• Design and build scalable solutions for distributed systems using microservices.
• Develop proof of concepts in Java as well as python for AI and GenAI solutions.
• Build high-quality, scalable, and efficient software solutions that brings GenAI capabilities, leveraging latest advancements such as Agentic LLM and RAG frameworks, etc. in GenAI space.
• Leverage third-party and in-house ML tools & OCI platform to develop reusable, highly performant machine learning systems with low-latency serving and reliable means to update/re-train ML models.
• Work collaboratively with cross-functional partners including product managers, operations team, and data scientists.
• Communicate continually with the project teams and explain progress on the development effort.
• Ensures quality of work through development standards and QA procedures.
• Keen on improvising technical solutions and processes emphasizing discovery through doing, iteration, and feedback loops.
• Identify opportunities for business impact, understand and prioritize requirements for machine learning systems and data pipelines, drive engineering decisions, and quantify impact.
• Attracts, grows, and develops the engineering team with builders and creators.