Craft cutting-edge custom software solutions designed to enhance and integrate various systems and applications. This role leverages modern frameworks and agile methodologies to deliver scalable, high-performance software tailored to unique business requirements, focusing on AI-native Oracle solutions.

We are seeking an AI-Powered Tech Talent AI Solution Architect / Application Lead to architect and implement AI-native Oracle solutions. You will be responsible for building and running bespoke AI applications and agents on OCI, personalized to customer data and Oracle Integration Cloud Service (ICS) processes.

Key responsibilities include designing and building custom Oracle AI solutions that enhance Oracle Integration Cloud Service (ICS) scenarios using OCI AI services and Oracle data platforms. You will implement RAG/agent patterns end-to-end, including ingestion, chunking/embeddings, vector search, reranking, and grounded generation with citations.

Further duties involve defining evaluation and quality gates, such as grounding checks, regression tests, and red-team prompts, integrating them into CI/CD pipelines for production readiness. You will also engineer secure-by-design deployments, managing OCI IAM policies, network isolation, secrets management, and audit logging. Additionally, you will oversee AI operations in production, focusing on SLOs, monitoring (latency, errors, token/cost), incident playbooks, and continuous optimization.

A minimum of 2-5 years of experience in custom software engineering is required, with a minimum of 3 years of direct experience in Oracle Integration Cloud Service (ICS). The ideal candidate possesses strong foundational knowledge in OCI Generative AI and Data Science, including vector databases and embeddings, alongside expertise in Oracle data integration and governance (PII classification, access control, lineage).

Essential skills include a strong engineering background within the Oracle Integration Cloud Service (ICS) domain to ground AI outputs in Oracle process/data context. Proficiency in LLMOps, encompassing prompt/version control, evaluation harnesses, monitoring, and FinOps cost controls, is also crucial. The candidate should demonstrate an ability to take Proofs of Concept (PoCs) to production with robust governance and reliability.