Job Description

LLM SAP ABAP TrainerAbout the RoleA leading organization at the intersection of AI and enterprise technology is seeking a skilled SAP ABAP Engineer with expertise in Large Language Models (LLMs) and AI methodologies. The ideal candidate will play a key role in integrating modern AI techniques into SAP solutions, shaping the future of enterprise training and development. This is a unique opportunity to work on cutting-edge projects that bridge traditional enterprise systems with AI-driven advancements.Job Responsibilities:

• Deliver specialized SAP and ABAP training sessions, incorporating both functional and technical perspectives.
• Develop and maintain training materials covering LLM methodologies such as Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).
• Collaborate with curriculum designers and technical teams to create engaging and up-to-date learning content.
• Provide hands-on mentoring and coaching, integrating real-world SAP ABAP scenarios with AI training techniques.
• Evaluate learner progress, offer detailed feedback, and recommend personalized improvement strategies.
• Assist in troubleshooting and optimizing learning methodologies to enhance training effectiveness.

Job Requirements:

• At least 3+ years of experience in SAP architecture, implementation, and ABAP programming.
• Familiarity with AI/ML techniques, including LLM training methodologies such as SFT and RLHF.
• Strong training and facilitation skills with the ability to effectively communicate complex technical concepts.
• Excellent written and verbal communication skills in English for developing structured training documentation.
• Strong problem-solving abilities with an analytical mindset to refine and optimize learning strategies.
• Collaborative mindset, comfortable working with cross-functional teams to align content with industry needs.

Search GuidanceMandatory Skills: SAP ABAP - 3 yrs, Artificial Intelligence OR LLM OR Machine Learning - 2 yrsTotal Years Of exp: 3+ years experience mandatoryOpportunity: Full-time, 4 - 5 hours (PST overlap)Notice Period: ImmediateNo Of Open Positions: 20

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