SAP Technical Consultant (Advanced)
Imizizi
Reference: JHB001606-Jaime-1
ESSENTIAL SKILLS
Kindly note that this role is for an AI Engineer in a SAP team.
1. Python Programming
- Strong understanding of Python syntax and principles of clean, reusable code.
- Understanding of Python frameworks and libraries e.g. Pandas and NumPy
2. AWS Lambda Functions
- Experience developing, deploying, and managing serverless applications using AWS Lambda
- Proficiency in writing unit and integration tests for AWS Lambda functions to ensure functionality, performance, and reliability.
3. Version Control with Git
- Experience with Git repositories and code management (e.g. GitHub)
- Proficiency in using Git for version control and collaboration.
4. Testing Frameworks
- Experience with testing tools like pytest for creating and maintaining unit tests.
- Ability to implement automated testing pipelines to ensure code reliability.
5. API Management
- API designing principles and best practices.
- Experience in working with RESTful APIs and understanding how to consume and create APIs.
- Familiarity with API management tools, such as Apigee, for efficient and secure API integration.
6. Cloud Platforms
- Understanding how to deploy application applications in AWS.
7. IDE And Tools
- Visual studio code
- GitHub Desktop
- PyCharm
- Jupyter Notebook
- Any additional responsibilities assigned in the Agile Working Model (AWM) Charter
ADVANTAGEOUS SKILLS
- Strong understanding of SQL and experience writing complex queries for data extraction and manipulation.
- Basic understanding of Large Language Models (LLMs) like GPT-4 and their applications.
- Familiarity with integrating LLM APIs (e.g., OpenAI, Hugging Face) into Python applications is a plus.
- Experience and Knowledge about SAP Analytics Stack and Tools.
- Experience in designing and creating data models within SAP Datasphere leveraging Python for data transformation tasks.
- Experience in developing and implementing data integration solutions to connect various data sources to SAP Datasphere using Python scripts and APIs.
- Implementing and managing infrastructure on AWS using Terraform.
- Understanding and experience with Generative AI use cases or projects
- Coaching and giving training to fellow colleagues and users when required.
- Problem solving capabilities.
- Strong presentation skills
RESPONSIBILITIES
- The AI Engineer is a versatile and highly skilled professional responsible for leveraging advanced data analytics, machine learning, and artificial intelligence techniques to drive business insights, optimize operations, and deliver innovative solutions.
- This role encompasses a wide range of responsibilities, from creating data mining architectures and statistical models to implementing AI-powered prompt engineering strategies.
1. Data Analytics and Modelling
- Create data mining architectures, models, and protocols to identify trends and patterns in large data sets across various business functions, including market economics, supply chain, marketing, and scientific research.
- Apply advanced statistical and data analysis methodologies to derive actionable insights that inform business decisions.
- Research and stay up to date with emerging data science principles, theories, and techniques to continuously enhance the organization's analytical capabilities.
2. Machine Learning and AI Integration
- Develop and implement machine learning (ML) or other artificial intelligence (AI) techniques to solve business problems and derive actionable insights.
- Architect and implement prompt engineering strategies, leveraging advanced Natural Language Processing (NLP) techniques, to guide and control the behavior of AI language models.
- Collaborate with cross-functional teams to refine the prompt generation process and align the AI system's output with broader organizational goals and user needs.
3. AI-Powered Content Generation
- Craft, refine, and optimize the generation of AI-generated text prompts to ensure they are contextually accurate, engaging, and relevant for a wide array of applications, from conversational agents to automated content creation.
- Apply machine learning methodologies, including training data curation, feature engineering, model evaluation, and hyperparameter tuning, to continually improve the performance of AI systems.
- Knowledge and experience with use of Large Language Models (LLM) and Retrieval Augmented Generation (RAG) pipelines
4. AI System Integration and Deployment
- Integrate AI systems and models into existing applications and processes, ensuring seamless integration and optimal performance.
- Develop strategies and frameworks for deploying AI solutions at scale, addressing challenges related to scalability, reliability, and security.
- Collaborate with software engineers and IT teams to ensure the successful implementation and maintenance of AI-powered systems.
5. Stakeholder Engagement and Collaboration
- Provide guidance and support to help the organization leverage data-driven decision-making and AI-enabled capabilities.
- Collaborate with subject matter experts and domain specialists to understand business requirements and translate them into effective AI solutions.
- By combining advanced data analytics, machine learning, and AI integration, the AI Engineer plays a crucial role in transforming the organization's data assets into innovative, AI-driven solutions that drive strategic decision making, operational excellence, and competitive advantage.
QUALIFICATIONS/EXPERIENCE
- Bachelor’s degree in Computer Science, Software Engineering, or similar qualification.
- 3+ years’ experience in developing in Python.
- Strong background in software development, mathematics, and good analytical and problem-solving skills.
- Experience in AI Solutions
Submit your CV to: ***email_hidden*** and Subject line
