Sr. Oracle Cloud HCM Developer; AI-Accelerated

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Job Title: Sr. Oracle Cloud HCM Developer (AI-Accelerated)

Duration: 12+ Months

Location: Hybrid Wilmington, MA (Preferred: 3 days onsite. Remote only if VERY strong—Only EST and CST candidates)

• Claude experience
• Live XSLT ability
• HDL debugging
• OIC orchestration depth

Design, build, deploy, and support high-throughput, AI-accelerated data exchanges between Oracle Cloud HCM and enterprise ecosystems, including payroll processors, benefits vendors, finance/ERP, identity & access management systems, data warehouses, and emerging AI/ML platforms. This role demands a builder's mindset: someone who doesn't just configure integrations, but engineers automated, self-healing, audit-ready pipelines that scale with organizational growth.

• Partner with business systems analysts to translate functional requirements, data mappings, and integration use cases into scalable technical designs.
• Architect inbound and outbound integration patterns using Oracle-native and hybrid approaches, HCM Extracts, HDL/HSDL, REST/SOAP APIs, FBDI, file-based integrations, and event-driven (Business Events / webhook) patterns.
• Author comprehensive Technical Design Documents with data lineage diagrams, error-handling matrices, volumetric analysis, and SLA definitions.
• Evaluate and recommend patterns based on data volume, latency requirements, and security constraints (real-time vs. batch vs. near-real-time).
• Design for idempotency, retry logic, and graceful degradation, every integration must be resilient by default.

• Develop HCM Extracts (BIP-based and fast formula driven) with optimized SQL and delivery configurations.
• Configure BI Publisher templates for outbound file generation, CSV, XML, fixed-width, with dynamic parameter-driven formatting.
• Build inbound data loads using HDL/HSDL with pre-validation logic, transformation layers, and automated error capture.
• Develop integration orchestrations in Oracle Integration Cloud (OIC) Gen 2/3 or equivalent middleware, connections, mapping, error handling, and scheduling.
• Implement robust transformation and validation logic (cross-field validation, referential integrity checks, business rule enforcement) before data hits HCM, shift-left on data quality.
• Configure encryption (PGP/GPG), compression, SFTP delivery, and content-server staging with automated file-naming conventions.
• Build Business Events subscribers for real-time integration triggers (new hire, termination, job change events).

• Leverage AI-assisted coding tools (Claude Code, Git Hub Copilot, or equivalent) to accelerate XSLT/XSL-FO template development, Groovy scripting in OIC, and HDL file generation, achieving 2-3x velocity without sacrificing correctness.
• Use AI to auto-generate unit test payloads, edge-case HDL files, and regression test datasets from existing data dictionaries and mapping specs.
• Apply AI for rapid TDD/runbook authoring, draft technical design documents, error-handling procedures, and handover documentation from integration specifications with human review and refinement.
• Build or adopt automated validation frameworks, AI-powered log parsers that triage HDL load errors, extract failures, and ESS job exceptions, surfacing root causes in minutes rather than hours.
• Develop self-documenting integrations, automated generation of data flow diagrams, field mapping matrices, and change-impact summaries from code/configuration artifacts.
• Create intelligent monitoring dashboards with anomaly detection for integration health, volume drift, timing anomalies, error rate spikes, not just reactive alert-and-fix.
• Automate release note generation and commit message standardization for integration deployments.

• Perform thorough unit testing with positive, negative, boundary, and volumetric test scenarios.
• Support SIT and UAT cycles in close coordination with HCM functional and technical teams.
• Build automated regression test suites for critical integrations, every deployment runs against a known-good baseline.
• Validate data integrity end-to-end: source system transformation HCM staging HCM tables downstream consumers.

• Diagnose HDL load errors (entity-level, attribute-level, referential) using import process logs, HCM Data Loader monitoring, and UCM content inspection.
• Troubleshoot HCM Extract failures, ESS job errors, BIP template issues, delivery channel failures, data-driven exceptions.
• Support defect triage with root-cause analysis discipline, distinguish data issues from configuration issues from platform issues.
• Automate recurring triage patterns, if you're solving the same category of issue three times, build a script or runbook that eliminates it permanently.