Adheres to all phases of the application software development lifecycle.JD for AI/ML Engineer – Generative AI About Application Software Engineering – Support Machine Learning Insights (SMLI) The Support Machine Learning Insights (SMLI) team within Oracle Application Software Engineering focuses on transforming Technical Operations and Customer Support through cutting-edge Artificial Intelligence solutions. The team leverages Generative AI, Large Language Models (LLMs), Agentic AI, and Machine Learning to build intelligent applications that automate support workflows, enhance operational efficiency, improve customer experience, and reduce business costs. We develop production-grade AI solutions that integrate with enterprise systems and drive innovation across Oracle's support ecosystem. JD for AI/ML Engineer – Generative AI About Application Software Engineering – Support Machine Learning Insights (SMLI) The Support Machine Learning Insights (SMLI) team within Oracle Application Software Engineering focuses on transforming Technical Operations and Customer Support through cutting-edge Artificial Intelligence solutions. The team leverages Generative AI, Large Language Models (LLMs), Agentic AI, and Machine Learning to build intelligent applications that automate support workflows, enhance operational efficiency, improve customer experience, and reduce business costs. We develop production-grade AI solutions that integrate with enterprise systems and drive innovation across Oracle's support ecosystem. Job Responsibilities 1. Design, develop, and deploy enterprise-grade Generative AI solutions using Java and modern AI/ML technologies. 2. Build production-ready AI agents and multi-agent systems to automate technical operations and customer support workflows. 3. Design and implement Retrieval-Augmented Generation (RAG) pipelines using Vector Databases and enterprise knowledge sources. 4. Develop scalable data ingestion pipelines for structured and unstructured enterprise data. 5. Integrate Large Language Models (LLMs) with enterprise applications using Java, REST APIs, and AI orchestration frameworks. 6. Develop and optimize prompt engineering and prompt management strategies to improve AI response quality and reliability. 7. Implement embedding generation, vector indexing, semantic search, and retrieval using Vector Databases. 8. Evaluate AI application performance using A/B testing, automated evaluation frameworks, and human feedback to continuously improve model quality. 9. Deploy, monitor, and optimize AI applications for production environments, ensuring scalability, security, and reliability. 10. Collaborate with product managers, architects, data scientists, and cross-functional engineering teams to deliver innovative AI-powered solutions. 11. Participate in code reviews, design discussions, troubleshooting, and release activities while following engineering best practices. Mandatory Skills 1. 3–7 years of software development experience with strong proficiency in Java. 2. Hands-on experience in AI/ML technologies and Generative AI application development. 3. Experience building and deploying production-grade AI Agents and Agentic AI solutions. 4. Strong understanding and implementation experience of Retrieval-Augmented Generation (RAG) architectures. 5. Hands-on experience with Vector Databases such as Oracle AI Vector Search, Pinecone, Milvus, ChromaDB, Weaviate, or FAISS. 6. Experience developing data ingestion pipelines for enterprise knowledge sources. 7. Strong understanding of Prompt Engineering and Prompt Management techniques. 8. Experience designing and developing Multi-Agent Systems using modern AI orchestration frameworks. 9. Strong proficiency in Python, APIs, and modern engineering stacks; working knowledge of Java/Scala/Go preferred. 10. Familiarity with AI evaluation methodologies, including A/B Testing, response quality evaluation, hallucination detection, and performance benchmarking. 11. Partner closely with Data Engineering, Cloud Engineering, Product, Security, Legal, and Architecture teams 12. Experience integrating AI services with enterprise applications using REST APIs. 13. Strong analytical, debugging, and problem-solving skills. 14. Excellent communication and collaboration skills. Preferred Skills - Deep understanding of Classical ML and Deep learning, NLP, GenAI - Experience with LangChain, LangGraph, or similar AI frameworks. - Experience with OCI Generative AI, OpenAI, Azure OpenAI, Anthropic Claude, or Google Gemini. - Knowledge of Docker, Kubernetes, and cloud-native deployments. - Exposure to MLOps, CI/CD pipelines, and AI model lifecycle management. - Experience working with Oracle Cloud Infrastructure (OCI). - Define clear OKRs, KPIs, and success metrics for AI engineering initiatives - Familiarity with observability and monitoring tools for AI applications. - Experience working in Agile/Scrum development environments. Self-Test Questions 1. Do you have 3–7 years of hands-on Java development experience? 2. Have you designed and deployed Generative AI or LLM-based applications in production? 3. Do you have hands-on experience building Retrieval-Augmented Generation (RAG) solutions using Vector Databases? 4. Have you built AI Agents or Multi-Agent Systems using frameworks such as LangGraph, or similar? 5. Do you have experience with Prompt Engineering, Prompt Management, and AI evaluation techniques such as A/B Testing? 6. Have you implemented data ingestion pipelines for enterprise AI applications? 7. Do you have experience deploying scalable AI applications on cloud platforms or Kubernetes? (Preferred) 8. Have you worked on AI solutions supporting Technical Operations, Customer Support, or Enterprise Automation? (Preferred) Role Details RoleAI/ML Engineer – Generative AI | Experience | 3–7 Years | | Location | Bangalore | | Work Mode | Hybrid | | Primary Skills | Java, AI/ML, Generative AI, LLMs, Agentic AI, RAG, Vector Databases, Prompt Engineering, Prompt Management, Multi-Agent Systems, Data Ingestion Pipelines, AI Evaluation (A/B Testing), REST APIs | ### Responsibilities Job Responsibilities 1. Design, develop, and deploy enterprise-grade Generative AI solutions using Java and modern AI/ML technologies. 2. Build production-ready AI agents and multi-agent systems to automate technical operations and customer support workflows. 3. Design and implement Retrieval-Augmented Generation (RAG) pipelines using Vector Databases and enterprise knowledge sources. 4. Develop scalable data ingestion pipelines for structured and unstructured enterprise data. 5. Integrate Large Language Models (LLMs) with enterprise applications using Java, REST APIs, and AI orchestration frameworks. 6. Develop and optimize prompt engineering and prompt management strategies to improve AI response quality and reliability. 7. Implement embedding generation, vector indexing, semantic search, and retrieval using Vector Databases. 8. Evaluate AI application performance using A/B testing, automated evaluation frameworks, and human feedback to continuously improve model quality. 9. Deploy, monitor, and optimize AI applications for production environments, ensuring scalability, security, and reliability. 10. Collaborate with product managers, architects, data scientists, and cross-functional engineering teams to deliver innovative AI-powered solutions. 11. Participate in code reviews, design discussions, troubleshooting, and release activities while following engineering best practices. Mandatory Skills 1. 3–7 years of software development experience with strong proficiency in Java. 2. Hands-on experience in AI/ML technologies and Generative AI application development. 3. Experience building and deploying production-grade AI Agents and Agentic AI solutions. 4. Strong understanding and implementation experience of Retrieval-Augmented Generation (RAG) architectures. 5. Hands-on experience with Vector Databases such as Oracle AI Vector Search, Pinecone, Milvus, ChromaDB, Weaviate, or FAISS. 6. Experience developing data ingestion pipelines for enterprise knowledge sources. 7. Strong understanding of Prompt Engineering and Prompt Management techniques. 8. Experience designing and developing Multi-Agent Systems using modern AI orchestration frameworks. 9. Strong proficiency in Python, APIs, and modern engineering stacks; working knowledge of Java/Scala/Go preferred. 10. Familiarity with AI evaluation methodologies, including A/B Testing, response quality evaluation, hallucination detection, and performance benchmarking. 11. Partner closely with Data Engineering, Cloud Engineering, Product, Security, Legal, and Architecture teams 12. Experience integrating AI services with enterprise applications using REST APIs. 13. Strong analytical, debugging, and problem-solving skills. 14. Excellent communication and collaboration skills. Preferred Skills - Deep understanding of Classical ML and Deep learning, NLP, GenAI - Experience with LangChain, LangGraph, or similar AI frameworks. - Experience with OCI Generative AI, OpenAI, Azure OpenAI, Anthropic Claude, or Google Gemini. - Knowledge of Docker, Kubernetes, and cloud-native deployments. - Exposure to MLOps, CI/CD pipelines, and AI model lifecycle management. - Experience working with Oracle Cloud Infrastructure (OCI). - Define clear OKRs, KPIs, and success metrics for AI engineering initiatives - Familiarity with observability and monitoring tools for AI applications. - Experience working in Agile/Scrum development environments. Self-Test Questions 1. Do you have 3–7 years of hands-on Java development experience? 2. Have you designed and deployed Generative AI or LLM-based applications in production? 3. Do you have hands-on experience building Retrieval-Augmented Generation (RAG) solutions using Vector Databases? 4. Have you built AI Agents or Multi-Agent Systems using frameworks such as LangGraph, or similar? 5. Do you have experience with Prompt Engineering, Prompt Management, and AI evaluation techniques such as A/B Testing? 6. Have you implemented data ingestion pipelines for enterprise AI applications? 7. Do you have experience deploying scalable AI applications on cloud platforms or Kubernetes? (Preferred) 8. Have you worked on AI solutions supporting Technical Operations, Customer Support, or Enterprise Automation? (Preferred) Role Details | Role | AI/ML Engineer – Generative AI | | --- | --- | | Experience | 3–7 Years | | Location | Bangalore | | Work Mode | Hybrid | | Primary Skills | Java, AI/ML, Generative AI, LLMs, Agentic AI, RAG, Vector Databases, Prompt Engineering, Prompt Management, Multi-Agent Systems, Data Ingestion Pipelines, AI Evaluation (A/B Testing), REST APIs | ### Qualifications Career Level - IC2 ### About the Company Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. 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