Senior SAP AI & ML Engineer

LUXOFT; Greater London; On-site; GBP 75,000 - 85,000; Full time

Job summary

A leading technology consulting firm in the UK is seeking a Senior SAP AI & ML Engineer to design and develop AI solutions integrated with SAP systems. Responsibilities include building and monitoring machine learning models, collaborating with functional teams, and ensuring secure cloud integrations. The ideal candidate possesses strong machine learning fundamentals, hands-on experience with MLP models, and expertise in SAP BTP. This role offers a unique opportunity to work on cutting-edge AI technologies in a dynamic environment.

Qualifications

• Strong knowledge of Machine Learning fundamentals, including supervised learning and model evaluation.
• Hands-on experience with MLP models, neural networks, and Python-based ML development.
• Expertise in SAP BTP, including AI Core, AI Launchpad, and integration services.

Responsibilities

• Design and develop SAP-based AI and ML solutions aligned with enterprise standards.
• Build, train, deploy, and monitor ML models for SAP business use cases.
• Integrate AI/ML solutions with SAP systems using APIs and OData services.

Skills

Machine Learning fundamentals

MLP models

Python-based ML development

Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn)

SAP BTP

REST APIs and OData

Version control and CI/CD best practices

SQL and data handling skills

Cloud platforms (AWS, Azure, GCP)

GenAI integration and MLOps

Job description

Project description

The SAP AI & ML platform enables enterprises to embed intelligent automation, predictive analytics, and AI-driven insights into SAP business processes using SAP S/4HANA, SAP BTP, and cloud-native AI services. As a Senior SAP AI & ML Engineer, you will work closely with SAP Architects, Data Scientists, and Business Stakeholders to design, develop, and integrate Machine Learning models (including MLPs) and AI services into SAP landscapes. You will leverage SAP coding standards, GitHub-based DevOps, SAP BTP AI services, and GenAI capabilities to optimize enterprise processes and enable data-driven decision-making. The consultant will work closely with functional teams, ABAP developers, and architects to deliver intuitive, secure, and high-performing user interfaces using SAP Fiori and SAP UI5.

Responsibilities

• Design and develop SAP-based AI and ML solutions aligned with enterprise architecture standards.
• Build, train, deploy, and monitor ML models (including MLPs) for SAP business use cases.
• Integrate AI/ML solutions with SAP systems (S/4HANA, BW, Datasphere) using APIs and OData services.
• Develop SAP applications using ABAP, CDS, RAP/CAP, and SAP BTP services.
• Implement GitHub-based version control, CI/CD pipelines, and DevOps practices.
• Collaborate with SAP Architects to ensure secure, scalable SAP and cloud integrations.
• Define security, access controls, and compliance for AI-enabled SAP solutions.
• Identify and assess AI integration opportunities and architectural impacts.
• Document solution architecture, ML pipelines, and integration patterns.
• Support existing SAP AI solutions through structured change and release management.
• Implement GenAI use cases to enhance SAP process intelligence and automation.
• Communicate technical risks and contribute to governance and change management processes.

SKILLS

Must have

• Strong knowledge of Machine Learning fundamentals, including supervised learning and model evaluation.
• Hands-on experience with MLP models, neural networks, and Python-based ML development.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in SAP BTP, including AI Core, AI Launchpad, and integration services.
• Experience integrating AI/ML models into SAP using REST APIs, OData, and microservices.
• Proficiency with GitHub, CI/CD pipelines, and DevOps practices.
• Strong SQL and data handling skills with SAP HANA.
• Knowledge of cloud platforms (AWS, Azure, or GCP) in SAP hybrid environments.
• Experience with GenAI integration and MLOps concepts including model deployment and monitoring.

Nice to have

• Strong stakeholder engagement and cross-functional collaboration skills.
• Excellent analytical and problem-solving abilities.
• Ability to mentor junior developers and share best practices.
• Strong communication and documentation skills.
• Agile/Scrum experience in enterprise delivery environments.