Forward Deployed Application/ML Engineering Expert

SAP
Riyadh
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Problem-solving","Critical thinking","Communication","Collaboration","Technical leadership"]

Design, build, and operate AI-native, cloud-native enterprise applications directly within customer environments. Translate ambiguous business and operational needs into secure, scalable architectures, owning delivery from discovery and prototyping through deployment, observability, and production handover. Develop and productionize AI capabilities using LLMs, RAG, and agentic workflows, applying evaluation frameworks and SAP-aligned architectural guardrails to enable responsible, trustworthy outcomes.

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FursaFursa
SAP
SAP
2 hours ago

Forward Deployed Application/ML Engineering Expert

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Last checked: 2 hours agoStatus: Live

Job Summary

Design, build, and operate AI-native, cloud-native enterprise applications directly within customer environments. Translate ambiguous business and operational needs into secure, scalable architectures, owning delivery from discovery and prototyping through deployment, observability, and production handover. Develop and productionize AI capabilities using LLMs, RAG, and agentic workflows, applying evaluation frameworks and SAP-aligned architectural guardrails to enable responsible, trustworthy outcomes.
Location: Riyadh
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, develop, and operate production-grade cloud-native enterprise applications integrating AI capabilities including LLMs, RAG, and agent-based workflows.
  • •Embed into customer projects and fast-moving cross-functional teams to understand business processes and technical landscapes.
  • •Translate business and product requirements into robust application architectures balancing speed, quality, security, and maintainability.
  • •Rapidly prototype, iterate, and productionize solutions in customer environments, adapting reference architectures and reusable assets.
  • •Own application delivery end-to-end from problem framing through deployment, observability, and production operations, ensuring milestones and technical objectives are met.
Travel: Low travel

Key Requirements

  • •Extensive hands-on experience in cloud-native enterprise and SaaS application engineering, with strong architectural knowledge across scalability, security, and reliability.
  • •Proven ability to design and deliver AI-native applications using large language models, RAG architectures, vector databases, and agentic systems.
  • •Strong proficiency in AI/ML Python libraries and frameworks, with exposure to data pipelines and MLOps practices.
  • •Experience integrating agentic AI into complex business processes to support responsible enterprise operations.
  • •Ability to collaborate cross-functionally with customers and stakeholders on complex technical topics and to communicate solution trade-offs and progress.
Experience:EnterpriseSaaSCloud-nativeAI/MLMLOpsVector databasesAgentic AI
Skills:Problem-solvingCritical thinkingCommunicationCollaborationTechnical leadership
Tech Stack:PythonCloud-nativeSaaSAIMLLarge language modelsLLMsRetrieval-augmented generationRAGVector databasesAgent-based workflowsAgentic systemsData pipelinesMLOpsObservabilitySAP AI CoreVectorizationJoule StudioRPT-1Business Data Cloud

Company Brief

SAP
Global enterprise software company best known for ERP systems and business applications covering finance, supply chain, procurement, HR, analytics, and customer management for large organizations.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Walldorf, Germany
Founded: 1972
Glassdoor
Glassdoor: 4.1
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