# NeerInfo Solutions — SAP AI Enterprise Architect

- Generated: 2026-09-22 09:31:29 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4470424368/
- Provider: LinkedIn
- Posted: approximately 2026-09-22 08:31 AM EDT (from '1 hour ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp when available
- Applicants: Be among the first 25 applicants
- Work model/location: Remote — United States
- Compensation: Not disclosed; Architect title does not qualify for the missing-compensation exception
- Travel: Not disclosed
- Positioning track: Technical IC
- Fit outcome: FAIL — 63%

## Direct-match strengths

Enterprise AI architecture, agents, RAG, knowledge graphs, Python, Kubernetes, cloud platforms, automation, observability, governance, and service reliability.

## Hard or material gaps

Hard technical-platform gap: the role requires deep SAP Basis/operations/managed-services experience plus SAP Joule, AI Core, BTP, Cloud ALM, Knowledge Graph, and SAP-centered AIOps/service-management architecture. Compensation is also undisclosed for a non-qualifying title.

## Evidence map

1. Enterprise AI architecture (weight 3, evidence 3/3) — Direct production AI-platform architecture.
2. Agents, RAG, and knowledge graphs (weight 2, evidence 3/3) — Direct supported evidence.
3. Python, Kubernetes, and cloud (weight 2, evidence 3/3) — Direct engineering depth.
4. SAP Basis and managed services (weight 3, evidence 0/3) — Not source-supported.
5. SAP Joule, AI Core, and BTP (weight 3, evidence 0/3) — Not source-supported.
6. SAP Cloud ALM and Knowledge Graph (weight 3, evidence 0/3) — Not source-supported.
7. Qualifying compensation (weight 2, evidence 0/3) — Undisclosed for an Architect title.

## Keyword diagnostic

Strong transferable AI-platform and AIOps-adjacent skills cannot replace mandatory SAP operations and SAP AI platform depth.

## Full normalized job description

Principal SAP AI Enterprise Architect – Agentic AI & Automation.
Location: Remote
Type: FTE
Role Summary
We are looking for a hands-on AI Architect to lead the design, development, and industrialization of AI, Agentic AI, and Automation solutions across SAP ERP Platform Managed Services. The role requires a practitioner who has built and deployed production-grade AI solutions, agents, and automation frameworks for enterprise Platform operations (SAP preferred).
Key Responsibilities
• Design and implement AI, Agentic AI, and automation solutions for SAP ERP Operations, AMS, and Platform Services.
• Build and operate AI platform components including orchestration services, agent gateways, agent lifecycle management, knowledge layers, and AI observability.
• Develop AI-powered use cases for incident management, RCA, transport management, job scheduling, monitoring, compliance, and self-healing operations.
• Design and train domain-specific agents and copilots using SAP Joule, SAP AI Core, Knowledge Graphs, BlueVerse AI models, and enterprise AI platforms.
• Implement event-driven architectures, APIs, microservices, and agent integrations using Kafka, REST, gRPC, and MCP patterns.
• Build and maintain RAG/GraphRAG solutions leveraging vector databases, enterprise search, and knowledge graphs.
Required Qualifications
• 10+ years of experience in enterprise platforms, cloud engineering, ERP operations, managed services, or software engineering.
• 3+ years of hands-on experience designing and implementing GenAI, Agentic AI, or enterprise AI solutions in production.
• Strong experience with SAP Basis, SAP Operations, ERP Managed Services, AIOps, Service Management, or enterprise support environments.
• Hands-on experience with SAP AI technologies such as SAP Joule, SAP AI Core, SAP BTP, SAP Cloud ALM, SAP Knowledge Graph, or related SAP Business AI capabilities.
• Experience building agent-based solutions using frameworks such as LangGraph, CrewAI, MCP architectures, OpenAI Agents, ADK, or equivalent.
• Hands-on experience with RAG, GraphRAG, vector databases, knowledge graphs, enterprise search, and LLM integration patterns.
• Strong experience with Kubernetes, Kafka, Python, API Gateways, microservices, CI/CD, Prometheus/Grafana, and observability tooling.

## Artifact metadata

- Resume: Not generated because the fit gate returned FAIL.
- Cover letter: Not generated because the fit gate returned FAIL.
- LinkedIn note: Not generated for a FAIL role.
- Google Drive used: No