As an AIML Engineer, you will be responsible for designing, developing, and deploying AI-powered applications and agentic AI solutions leveraging Python, LangChain, LangGraph, LLMs, RAG, Oracle Database 23c/26ai, and Oracle APEX. You will work closely with cross-functional teams to build scalable AI solutions that integrate enterprise data, intelligent agents, and modern application interfaces to solve complex business problems.

Responsibilities :

- Agentic AI Development : Design, develop, and deploy AI-powered applications and intelligent agents using Python, LangChain, and LangGraph to solve complex business use cases.

- LLM Integration : Configure and integrate Large Language Models (LLMs) with Oracle-based applications and enterprise data, enabling intelligent search, conversational AI, automation, and decision-support capabilities.

- RAG Architecture : Design and implement Retrieval-Augmented Generation (RAG) solutions, integrating enterprise data and retrieval mechanisms with LLM-powered applications within the Oracle Database 23c/26ai ecosystem.

- Oracle AI Development : Leverage Oracle Database capabilities to build AI applications that combine enterprise data, vector search, LLMs, and intelligent application workflows.

- Oracle APEX Development : Build intuitive and interactive application interfaces, dashboards, and reports using Oracle APEX.

- SQL & PL/SQL Development : Develop efficient SQL queries, stored procedures, functions, packages, and other database components using SQL and PL/SQL.

- AI Application Integration : Integrate Python-based AI services and agentic workflows with Oracle databases and APEX applications to deliver end-to-end AI solutions.

- Solution Engineering : Design scalable and production-ready AI architectures that bring together LLMs, RAG, agentic frameworks, Oracle databases, and application interfaces.

- Performance & Optimization : Optimize AI applications, database queries, RAG pipelines, and agentic workflows for performance, scalability, reliability, and maintainability.

- Cross-Functional Collaboration : Work closely with Consulting, Engineering, Data Science, and other teams to translate business requirements into practical Oracle AI solutions.

- Client Engagement : Collaborate with clients and stakeholders to understand business requirements, demonstrate Oracle AI capabilities, and identify opportunities for AI-led transformation.

What do we expect?

- Python & Agentic AI Expertise : Strong hands-on experience developing Python applications using agentic AI frameworks such as LangChain and LangGraph.

- Generative AI & LLM Expertise : Experience integrating and configuring LLMs for enterprise AI use cases, including conversational AI, intelligent automation, and AI agents.

- RAG Expertise : Proven experience designing and implementing RAG architectures, including embeddings, vector search, document/data retrieval, context management, and LLM integration.

- Oracle Database Expertise : Hands-on experience with Oracle Database 23c/26ai, with a strong understanding of Oracle's AI and vector capabilities.

- Oracle APEX : Strong hands-on experience with Oracle APEX for building application interfaces, dashboards, forms, and reports.

- SQL & PL/SQL : Strong proficiency in SQL and PL/SQL, including complex queries, stored procedures, functions, packages, and database optimization.

- AI & Database Integration : Experience integrating AI/LLM applications with enterprise databases and leveraging structured and unstructured data for AI solutions.

- Problem-Solving Mindset : Strong analytical and problem-solving skills, with the ability to translate complex business requirements into scalable AI solutions.

- Communication Skills : Excellent communication and collaboration skills, with the ability to explain AI, database, and application concepts to both technical and non-technical stakeholders.

- Productionization : Experience deploying and maintaining AI applications in enterprise environments with an emphasis on security, scalability, performance, and reliability.