As a Technology Platform Engineer, you will be instrumental in crafting and deploying production and non-production cloud environments. This involves leveraging essential software tools to build robust platforms for projects and products. A key aspect of this role is the automation of the deployment pipeline, ensuring efficient and consistent environment creation and configuration.

You will architect and deliver AI-native Oracle solutions, building and running bespoke AI applications and agents on OCI tailored to specific customer data and Oracle Financial Consolidation and Close (FCC) processes. This role demands a deep understanding of AI integration within the Oracle ecosystem.

Design and construct custom Oracle AI solutions that enhance Oracle Financial Consolidation and Close (FCC) scenarios by 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.

Establish evaluation metrics and quality gates, including grounding checks, regression tests, and red-team prompts, integrating them 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.

Manage AI operations in production, defining SLOs, implementing monitoring for latency, errors, and token/cost, developing incident playbooks, and driving continuous optimization.

A minimum of 3 years of hands-on experience is essential for this role.

Possess strong foundational knowledge in OCI Generative AI and Data Science, including vector databases and embeddings. Expertise in Oracle data integration and governance, covering PII classification, access control, and lineage is required.

Demonstrate strong engineering proficiency within the Oracle Financial Consolidation and Close (FCC) domain to ensure AI outputs are accurately grounded in Oracle process and data context.

Familiarity with LLMOps practices, including prompt and version control, evaluation harnesses, monitoring, and FinOps cost controls is expected. The ability to take Proofs of Concept (PoCs) to production with governance and reliability is also a key requirement.