AI/ML Automation Engineer – SAP

Role: AI/ML Automation Engineer - SAP
Location: Sunnyvale, CA/Austin, TX (Onsite)
Duration: 6 months contract

Job Description:
We are seeking an Automation + AI/ML Engineer with strong SAP experience, particularly in SAP SD, to design and deliver intelligent automation solutions across SAP and non-SAP enterprise systems.

Key Responsibilities

• Design and develop AI/ML and GenAI-powered automation solutions for enterprise business processes.
• Build AI agents and intelligent workflows using LLMs and Generative AI technologies.
• Develop REST API-based automation and testing across SAP and non-SAP applications.
• Integrate LLMs into enterprise applications, including API integration, prompt engineering, RAG/retrieval workflows, and GenAI solution development.
• Work with SAP SD and understand integrations with SAP MM and FI.
• Analyze business requirements and translate them into functional and technical specifications.
• Understand SAP validations, ABAP-based implementations, and SAP S/4HANA processes.
• Collaborate with business stakeholders, SAP functional/technical teams, API developers, and automation teams.
• Lead technical discussions and workshops and drive solutions through design, development, testing, and deployment.
• Design scalable and reliable AI/automation solutions aligned with enterprise architecture and business objectives.

Required Skills

• 8–10 years of experience in SAP, Automation, AI/ML, or related enterprise technology.
• Strong hands-on experience with SAP SD.
• Good understanding of SAP MM/FI integrations.
• Strong experience with Generative AI, LLMs, AI agents, and intelligent automation.
• Experience with prompt engineering, RAG/retrieval workflows, and LLM APIs.
• Strong REST API development, integration, automation, and testing experience.
• Understanding of SAP S/4HANA, ABAP validations, and enterprise integration architecture.
• Strong problem-solving, communication, and stakeholder management skills.

Preferred / Nice to Have

• Experience with Docker and Kubernetes.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience designing enterprise-scale AI/automation architectures.
• Exposure to Apple ecosystem projects.
• Experience leading workshops and guiding technical teams.