Join Accenture as a Database Administrator, focusing on architecting and delivering cutting-edge AI-native Oracle solutions. This role involves building and managing bespoke AI applications and agents on OCI, tailored to specific customer data and Oracle Procurement Cloud processes. You'll be instrumental in transforming business operations through the responsible application of AI and data science.

This is an opportunity to be a catalyst in the technology space, leveraging advanced technologies to reinvent how businesses operate. You will be at the forefront of creating the tech foundations that drive future business transformations, contributing to positive global change.

Design and build custom Oracle AI solutions that enhance Oracle Procurement Cloud scenarios, utilizing OCI AI services and Oracle data platforms. Implement end-to-end RAG/agent patterns, covering ingestion, chunking, embeddings, vector search, reranking, and grounded generation with citations.

Define and integrate evaluation and quality gates, including grounding checks, regression tests, and red-team prompts, into CI/CD pipelines before go-live. Engineer secure-by-design deployments, focusing on OCI IAM policies, network isolation, secrets management, and audit logging for production readiness.

Operate AI in production environments by managing SLOs, monitoring performance (latency, errors, token/cost), developing incident playbooks, and driving continuous optimization efforts.

A minimum of 3 years of experience is required, with a preference for candidates with 2-5 years in database administration. Must possess strong skills in Oracle Procurement Cloud.

Candidates should have a solid foundation in OCI Generative AI and Data Science, including proficiency with vector databases and embeddings. Expertise in Oracle data integration and governance, encompassing PII classification, access control, and lineage, is essential.

Demonstrated engineering strength within the Oracle Procurement Cloud domain is critical to ground AI outputs in relevant process and data context. Experience with LLMOps, including prompt/version control, evaluation harnesses, monitoring, and FinOps cost controls, is highly valued. The ability to take Proofs of Concept (PoCs) to production with robust governance and reliability is also a key requirement.