cmathgit

Software / Integration Engineer • Oracle Integration Cloud • Oracle Fusion Cloud ERP • Computer Science • Mathematics

Software / Integration Engineer: Oracle Integration Cloud & Oracle Fusion Cloud ERP (SCM/FIN/HCM) — building, testing, and maintaining enterprise integrations and technical extensions supporting Oracle Fusion Cloud ERP under Kanban AGILE methodology and change control management. M.S. Computer Science — Cybersecurity & Digital Forensics, EKU 2023. B.S. Mathematical Sciences, NIU 2016.

Views expressed are my own and do not represent any employer. Content is solely to spread the Gospel of Jesus Christ through technology, musicianship, art, and media. I receive zero compensation from any entity for products or services shared. Full disclaimer ↓

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Oracle Integration Cloud (OIC) & Oracle Cloud Infrastructure (OCI) Enterprise Integration Engineering

Design and support integration solutions for Oracle Fusion Cloud ERP (SCM/FIN/HCM) via Oracle Integration Cloud (OIC) Gen3 under a change-control management governed delivery model. Each change documents business purpose, affected users, master data/configuration impact, environment-specific testing, approvals, and post-production follow-up. Technologies: OIC Gen3, REST/SOAP APIs, Oracle ATP, BI Publisher, FBDI, ESS, PL/SQL, Java, XML, and SFTP.

Surgical Case Management & Clinical Procurement Integration

  • Engineered a bidirectional clinical procurement data exchange between an external EMR platform and Oracle Fusion ERP.
  • Outbound (ERP → EMR): Two BI Publisher interfaces — Item Master extract and PO lifecycle extract — published via SFTP to the EMR on automated schedules.
  • Inbound (EMR → ERP): OIC Gen3 orchestration ingesting purchase requisitions via SFTP, staged in ATP, enriched with ERP reference data via BI Publisher lookups, and submitted through FBDI and ESS job orchestration.
  • SOC 2-compliant fault handling, record-level ATP status tracking (NEW / SUCCESS / ERROR), and automated scheduling.
  • Coordinated with case schedule, case usage, and contract price data managed within the EMR platform to ensure end-to-end surgical case and procurement workflows.

Capital Budget Integration (FBDI & ESS)

  • OIC Gen3 scheduled orchestration ingesting daily capital project and budget extracts from an external EPM platform via SFTP.
  • Parses pipe-delimited data into ATP staging tables (project headers, task details, budget records).
  • Enriches records with Oracle reference data via BI Publisher lookups for project ownership and cost center resolution, both required by Oracle Fusion Project Management FBDI.
  • Constructs Oracle-standard FBDI control files for projects and budgets and submits to Oracle Fusion Project Control via ESS: Load Interface File for Import → Import Projects → Import Project Budgets.
  • De-duplication, version-aware budget update logic, partial-success fallout handling, batch-level email notifications, and SFTP-based FBDI archiving for audit.
  • Fault handling for SFTP, ATP, REST, and SOAP connections; monitors and confirms ESS job completion with wait/retry logic.

Invoice Order Attachment Integration

  • OIC Gen3 orchestration ingesting daily zipped invoice image containers (~500 invoices/day) from an external healthcare supply chain provider via SFTP.
  • Parses the index file to stage invoice metadata in ATP; resolves Oracle invoice IDs via BI Publisher data model lookup.
  • Dynamically constructs REST POST payloads with base64-encoded PDFs and invokes the Oracle Fusion Cloud Payables attachments endpoint.
  • Orphan PDF detection, record-level SUCCESS/ERROR status tracking, CSV error reporting, and SFTP archiving per batch run.
  • Global and local fault handling across SFTP, ATP, and REST connections.

OIC AI Integration Demo — AP Invoice Intelligence Pipeline

  • Proof-of-concept multi-model AI pipeline built inside OIC Gen3, connecting three external AI providers via REST Adapter invokes to perform OCR extraction, semantic embedding, duplicate detection, and AP analyst summarization against vendor invoice PDFs.
  • Pass 1 — Plain-Text OCR + Semantic Embedding: Each invoice PDF is base64-encoded and submitted to an OCR endpoint. The string is passed to an embeddings API producing a semantic vector stored in ATP. Duplicate detection uses cosine similarity via VECTOR_DISTANCE() against previously stored invoice vectors.
  • Pass 2 — Structured JSON Extraction: A second OCR call enforces strict JSON-only output. A reusable OIC JavaScript action extracts nested fields using dot-notation path expressions, enabling clean mapping into OIC flow variables and ATP staging columns.
  • Pass 3 — AP Analyst Summarization: The structured JSON invoice payload is submitted to a chat completions endpoint via OIC REST Adapter invoke using an AP audit-focused system prompt. The response is stored in ATP for AP analyst consumption.
  • Validated field extraction schema and provider portability — each external model endpoint is independently replaceable with an OCI Generative AI endpoint by updating the connection target URL and Bearer token only.
  • All AI calls logged centrally with model name, token consumption, call latency, pipeline status, and estimated cost per invoice, supporting a daily AI cost summary email and full observability.

SFTP Migration — SCM OIC Refactor

  • Refactored OIC file-polling orchestrations for SCM integrations to redirect inbound file acquisition from a decommissioned on-premises SFTP server to a vendor-hosted endpoint by inserting an OIC FTP/SFTP invoke step at the boundary layer.
  • Preserved all downstream ATP staging, FBDI construction, and ESS orchestration logic without rewriting existing integration flows.
  • Migrated seven outbound BI Publisher-scheduled SCM interfaces into OIC-managed schedulers to resolve a non-standard port incompatibility preventing direct BI Publisher SFTP delivery.
  • Maintained identical file contracts with the external system and added ad hoc BI Publisher output pickup logic for business continuity.

SCM Middleware Error Notification Remediation

  • During SFTP migration analysis, identified a silent-failure defect in OIC Shipping and Receipt import integrations where middleware errors produced no email notifications due to missing email body mappings in the shared error-handler switch condition.
  • Escalated during stand-up, received team approval to expand scope within the same delivery window, and implemented the targeted fix restoring full operational alerting for production middleware failures.
  • Resolved without redesigning the shared error framework, preserving all other integration flows downstream.

SCM Integration RCA & Stabilization (>99% Error Reduction)

  • Served as OIC SME for post-go-live stabilization following enterprise legacy ERP to Oracle Fusion Cloud ERP migration.
  • Gap Remediation: Performed comparative analysis of legacy SCM transaction semantics versus Oracle Fusion Receiving interface constraints, identifying undocumented dependencies in supplier site attribution, item-org UOM compatibility, and PO lifecycle synchronization.
  • Middleware Enhancements: Refactored inbound OIC integrations to introduce ATP-based canonical staging and BI Publisher-driven enrichment prior to FBDI/REST submission.
  • RCA Methodology: Established root cause analysis processes leveraging OIC instance logs, ESS request history, and ATP staging table queries to deterministically differentiate Oracle configuration defects from upstream data-quality violations.
  • Outcomes: Reduced monthly SCM receipt middleware errors by over 99% and Oracle cloud receiving errors by approximately 98% following post-go-live stabilization.
  • Operational Support: Authored production support playbooks enabling operations teams to locate, re-stage, and reprocess failed SCM transactions without manual ERP intervention.

OCI PaaS Optimization

  • Reduced infrastructure costs by automating OIC and ATP instance shutdown/startup schedules for off-hours.
  • Reduced the number of active OIC Connectivity Agents in test environments.
  • Maintained DR environments in standby mode, activating only for production backups or disaster recovery events.
  • Significantly lowered compute costs while preserving operational readiness across all environments.

OpenWebUI Deployment & Local LLM Integration

  • Self-hosted generative AI platform centered on OpenWebUI as a unified orchestration layer for locally hosted SLMs, GGUF inference, and cloud-based LLMs. Supports coding assistance, agentic CLI workflows, Bible study, text/music/image generation, OCR/document analysis, and RAG while maintaining local control over chats, prompts, and files.
  • Tools: Wolfram Alpha LLM API, KJV Bible verse retrieval, Verse of the Day via BibleGateway, web search, OCR, embedding, reranking, and RAG pipelines. Deterministic injection for token optimization bypasses the LLM for retrieval tasks.
  • Features: RAG pipelines, MCP servers, multi-agent workflows, and Role-Pseudonymous Prompting (RPP) privacy protocol. Paired with Continue for IDE-centered coding and agentic development workflows.
  • Benchmarks: Open-access LLMs with optimized RAG/Embedding pipelines achieve A+ parity with flagship models at 94.4% cost reduction. Replaces a ~$48–$77/month paid tool stack at $0 recurring cost.

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Disclaimer: Views expressed on this page are my own and do not represent my employer, current nor former. This applies to any and all posts and interactions on this platform both past and future. Content not intended for SEO-Spam/spamdexing/AI Slop or otherwise — solely to spread the Gospel of Jesus Christ through musicianship, art, technology, and media. I receive zero compensation from any entity for any products or services shared — any perceived promotion material is a result of organic personal interest. Read the full disclaimer: Statement of Copyright Protection  |  Content Disclaimer & Liability Limitations

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Statement of Copyright Protection for Music by cmathgit

© 2026 cmathgit. All rights reserved.

1. Copyright Protection Statement for music that is 100% human authored.
This musical work is 100% authored, created, and composed exclusively by human effort, without the use of artificial intelligence, machine-generated content, or automated tools. Unauthorized duplication, distribution, broadcasting, public performance, adaptation, sampling, or use in derivative works is strictly prohibited unless expressly authorized in writing by the copyright holder.

2. Copyright Protection Disclaimer for music authored using AI/LLM assisted tools.
Ownership and commercial use rights are retained for any songs generated by myself using Suno during active subscription, even after cancelling. Proof of ownership is available upon request. For more information, please reference Suno Knowledge Base Articles at help.suno.com.

Copyright protection in AI-assisted music increases with substantial human creative input. Musicians should maximize their original contributions, clearly positioning the AI as an assistive tool rather than the primary creator. Current copyright law continues to prioritize human creativity, even as technology evolves.

Full statement: Statement of Copyright Protection  |  Content Disclaimer & Liability Limitations