Total-TECH Co.
” The Job Description”
1. Design, develop, and implement AI/ML models that enhance the procurement process, including
forecasting, automated approvals, risk assessment, and supplier recommendations.
2. Develop and integrate AI-driven chat assistants to support procurement users with real-time
guidance and recommendations.
3. Implement retrieval-augmented generation (RAG) techniques to create AI systems that retrieve
and generate relevant information for user queries, ensuring precise and contextual responses.
4. Work with product and engineering teams to integrate AI solutions, including chat assistants and
RAGs, into the existing product architecture.
5. Develop algorithms for data analysis, pattern recognition, and automation to improve
procurement workflows.
6. Collaborate with cross-functional teams to identify opportunities for AI-driven improvements in
user experience, decision-making, and process efficiency.
7. Ensure AI solutions are scalable, secure, and maintainable, with a focus on performance and
accuracy.
8. Stay updated with the latest AI/ML technologies and best practices, including chat and RAG
developments, and apply them to our product development.
9. Conduct A/B testing, performance tuning, and continuous improvement of AI models.
10. Provide technical leadership and guidance in AI/ML best practices.
Requirements:
● 2+ years of experience in AI/ML development and deployment in a production environment.
● Proficiency in one programming languages such as Python, JavaScript, or C++.
● Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
● Experience developing chat assistants or conversational AI systems.
● Familiarity the retrieval-augmented generation (RAG) techniques and relevant tools.
● Strong understanding of data processing, feature engineering, and model evaluation techniques.
Nice to have:
● Strong knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and AI/ML services.
● Knowledge of reinforcement learning, predictive analytics, or RAG models as applied to business
processes.
● Experience working with large datasets, ideally in procurement, supply chain, or a related field.