Home › Companies › Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 › Agentic AI Architect
Agentic AI Architect
Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 · Jersey City, New Jersey, United States; US New Jersey (JCO) C79 · Hybrid · Active · Oracle Recruiting Cloud / Fusion HCM
Job facts
| Field | Value |
|---|---|
| Company | Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 |
| Title | Agentic AI Architect |
| Normalized title | - |
| Department / team | Data Analytics |
| Location | Jersey City, NJ, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
| Posted / first seen | 2026-06-03 / 2026-06-04 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Oracle Recruiting Cloud / Fusion HCM. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Jersey City. | Open |
| Department jobs | Active postings in Data Analytics. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 |
| Source | 907773df-d032-42dc-b60a-978734f5ac21 |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
Description
Description
Technical skills :
GenAI & Agentic Frameworks - Semantic Kernel/ LangGraph (or similar orchestration frameworks); LLM integration (Azure OpenAI, OpenAI APIs, etc.); Prompt engineering, prompt lifecycle design
Retrieval & RAG - Azure AI Search (indexing, vector search, hybrid search); Embedding pipelines and retrieval optimization; RAG design, grounding strategies, context management
Tool Access & Integration - MCP (Model Context Protocol) architecture and tool design; API design (FastAPI / REST / microservices); Integration with enterprise systems and third-party APIs
AI Safety & Governance - NVIDIA NeMo Guardrails;Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control
Evaluation & ModelOps - Azure AI Foundry (model hosting, versioning, monitoring); Evaluation frameworks (LLM-as-judge, test datasets); Prompt/version control, cost/latency monitoring
DevOps & Observability - CI/CD pipelines (Azure DevOps / GitHub Actions); Logging, monitoring, observability (App Insights, etc.); Performance tuning and scalability
Responsibilities
Role & Responsibilities Overview:
Architecture & Technical Leadership Define end-to-end architecture for agentic AI-enabled platform across data, AI, orchestration, and integration layers with some real hands-on experience doing POCs Design and govern agentic orchestration framework for multi-step production workflows Establish architecture patterns for - RAG and grounding, Vector search and retrieval, MCP tool access layer, prompt management and evaluation Have a deep understanding of Agentic coding and best practices of using Agentic coding for large scale implementations Familiarity in implementing A2A or similar frameworks in a large scale environment Platform & Integration Design Define integration architecture across - Lakehouse, ODS, document systems, Underwriting systems and third-party APIs Design configurable, metadata-driven framework for multi-LOB onboarding Define API/microservices patterns (Python/.NET hybrid) AI & GenAI Enablement Define where and how to use - GenAI vs deterministic logic, agentic workflows vs pipeline workflows Establish multimodal integration approach combining structured, unstructured, and external data Design prompt lifecycle, evaluation, and optimization strategy Governance, Safety & ModelOps Define AI safety and guardrails (PII, hallucination control, policy constraints) Establish ModelOps and PromptOps frameworks Ensure explainability, auditability, and traceability of AI outputs Program Leadership Lead technical execution across AI, data, and platform teams Guide engineers (AI, data, full-stack) and ensure alignment with architecture Drive technical decisions and stakeholder communication
Qualifications
Education : Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field
Full job record
| Job ID | 08ae2af723a2555840bcdf86e58cec3954340856 |
| Org ID | 3ea3b397-9a23-408a-8421-50fd1d902746 |
| Source ID | 907773df-d032-42dc-b60a-978734f5ac21 |
| Board ID | 907773df-d032-42dc-b60a-978734f5ac21 |
| Provider | oracle_hcm |
| Provider Job Key | 14123 |
| Title | Agentic AI Architect |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Jersey City, New Jersey, United States; US New Jersey (JCO) C79 |
| Department | Data Analytics |
| Team | — |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NJ |
| City | Jersey City |
| Salary Raw | Description Technical skills : GenAI & Agentic Frameworks - Semantic Kernel/ LangGraph (or similar orchestration frameworks); LLM integration (Azure OpenAI, OpenAI APIs, etc.); Prompt engineering, prompt lifecycle design Retrieval & RAG - Azure AI Search (indexing, vector search, hybrid search); Embedding pipelines and retrieval optimization; RAG design, grounding strategies, context management Tool Access & Integration - MCP (Model Context Protocol) architecture and tool design; API design (FastAPI / REST / microservices); Integration with enterprise systems and third-party APIs AI Safety & Governance - NVIDIA NeMo Guardrails;Microsoft Presidio (PII detection/masking); Guardrails for prompt injection, hallucination control Evaluation & ModelOps - Azure AI Foundry (model hosting, versioning, monitoring); Evaluation frameworks (LLM-as-judge, test datasets); Prompt/version control, cost/latency monitoring DevOps & Observability - CI/CD pipelines (Azure DevOps / GitHub Actions); Logging, monitoring, observability (App Insights, etc.); Performance tuning and scalability Responsibilities Role & Responsibilities Overview: Architecture & Technical Leadership Define end-to-end architecture for agentic AI-enabled platform across data, AI, orchestration, and integration layers with some real hands-on experience doing POCs Design and govern agentic orchestration framework for multi-step production workflows Establish architecture patterns for - RAG and grounding, Vector search and retrieval, MCP tool access layer, prompt management and evaluation Have a deep understanding of Agentic coding and best practices of using Agentic coding for large scale implementations Familiarity in implementing A2A or similar frameworks in a large scale environment Platform & Integration Design Define integration architecture across - Lakehouse, ODS, document systems, Underwriting systems and third-party APIs Design configurable, metadata-driven framework for multi-LOB onboarding Define API/microservices patterns (Python/.NET hybrid) AI & GenAI Enablement Define where and how to use - GenAI vs deterministic logic, agentic workflows vs pipeline workflows Establish multimodal integration approach combining structured, unstructured, and external data Design prompt lifecycle, evaluation, and optimization strategy Governance, Safety & ModelOps Define AI safety and guardrails (PII, hallucination control, policy constraints) Establish ModelOps and PromptOps frameworks Ensure explainability, auditability, and traceability of AI outputs Program Leadership Lead technical execution across AI, data, and platform teams Guide engineers (AI, data, full-stack) and ensure alignment with architecture Drive technical decisions and stakeholder communication Qualifications Education : Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/14123 |
| Apply URL | https://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/14123 |
| First Seen At | 2026-06-04 10:44:42Z |
| Last Seen At | 2026-06-06 11:44:11Z |
| Last Checked At | 2026-06-06 11:44:11Z |
| Last Changed At | 2026-06-06 11:44:11Z |
| Inactive At | — |
| Source Posted At | 2026-06-03 16:45:37Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=oracle_hcm/board=fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com|cx_2/date=2026-06-06/2026-06-06T11-42-28-116Z-9f6f0c60410cbd3bee6b0a060a8e65cb535d3b1d1066f0984f31827798e22ea6.json |
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