Architect and deploy cutting-edge AI-native Oracle solutions, crafting bespoke AI applications and agents on OCI. These solutions will be meticulously tailored to specific customer data and Oracle Order Management processes.

This role involves building and running intelligent systems that enhance Oracle Order Management functionalities through the strategic application of OCI AI services and Oracle data platforms.

Design and implement custom Oracle AI solutions that significantly improve Oracle Order Management scenarios. This includes leveraging OCI AI services and robust Oracle data platforms.

Lead the end-to-end implementation of RAG/agent patterns, covering ingestion, chunking, embeddings, vector search, re-ranking, and grounded generation with precise citations.

Define and integrate comprehensive evaluation and quality gates, such as grounding checks, regression tests, and red-team prompts, into CI/CD pipelines for seamless go-live processes.

Engineer secure-by-design deployments, incorporating OCI IAM policies, network isolation, secrets management, and audit logging to ensure production readiness.

Manage AI operations in production environments, focusing on SLOs, continuous monitoring of latency, errors, token usage, and costs, alongside developing incident playbooks and driving ongoing optimization.

A solid foundation in OCI Generative AI and Data Science, including expertise in vector databases and embeddings.

Proficiency in Oracle data integration and governance, encompassing PII classification, access control, and lineage management.

Strong engineering skills within the Oracle Order Management domain are essential to ensure AI outputs are accurately grounded in Oracle process and data contexts.

Experience with LLMOps is required, including prompt and version control, evaluation harnesses, monitoring, and FinOps cost controls.

Demonstrated ability to take Proofs of Concept (PoCs) to production with a focus on governance and reliability, aligned with the required experience level.