• Review and refine AI-generated outputs related to digital transformation, organizational change, technology adoption, and practical aspects of transformation processes • Evaluate AI responses for operational accuracy, practicality, and compliance with real-world requirements • Draft realistic digital transformation scenarios based on your direct professional experience • Create scenario variations from different perspectives (e.g. transformation manager, client, stakeholder, or vendor) • Identify gaps, oversights, or weak reasoning in AI-generated transformation content

• Review and refine AI-generated outputs related to growth marketing strategy, campaign execution, funnel optimization, and practical aspects of growth marketing work • Evaluate AI responses for strategic value, practicality, and compliance with real-world marketing practices • Draft realistic growth marketing scenarios based on your direct professional experience • Create scenario variations from different perspectives (e.g. growth marketeer, product manager, client, or agency partner) • Identify gaps, oversights, or weak reasoning in AI-generated marketing content

Role Description We are seeking AI/ML Interns to join our AI & Innovation team. Our team is building the next generation of intelligent procurement solutions, leveraging Agentic AI, Retrieval-Augmented Generation (RAG), large language models (LLMs), and other cutting-edge AI technologies to transform how organizations manage sourcing and spend. As an intern, you will contribute to real AI projects from day one: - Designing and building RAG pipelines - Prototyping agentic workflows - Integrating LLMs into our product ecosystem You will collaborate closely with our engineering and data science teams to bring AI-driven features from concept to production. You will start working on meaningful AI projects right away. Qualifications - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field. - Strong programming skills in Python; familiarity with AI/ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, or scikit-learn. - Exposure to LLM frameworks and tools (e.g., LangChain, LlamaIndex, OpenAI API, or similar) is a plus. - Foundational understanding of machine learning concepts, NLP, and deep learning architectures. - Familiarity with vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS) and embedding techniques is a plus. - Excellent communication, organization, and interpersonal skills with a genuine curiosity about emerging AI technologies. - Relevant coursework or personal projects in AI, machine learning, or NLP are highly valued. Requirements - Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases, embedding models, and LLM APIs. - Prototype and build agentic AI workflows that autonomously plan, reason, and execute multi-step tasks within our procurement platform. - Evaluate and benchmark LLMs and AI models for accuracy, latency, cost, and relevance across different procurement use cases. - Develop and refine prompt engineering strategies to improve the quality and reliability of LLM-generated outputs. - Build data ingestion and preprocessing pipelines to prepare enterprise documents for embedding and retrieval. - Research emerging AI techniques (e.g., function calling, multi-agent orchestration, fine-tuning) and present findings to the team. - Contribute to our library of reusable AI components, tools, and integration patterns. - Participate in demos and feedback sessions to validate AI features with internal stakeholders and customers. - Document AI experiments, model performance metrics, and architectural decisions to build our team’s knowledge base. Benefits - Great medical plans - Adoption benefits - Wellness reimbursement - Generous parental leave - 401(k) match - Flexible work environment - No limit vacation days for exempt employees - Much more!

• The Senior Analyst, AI Transformation is a hands-on builder who designs and deploys AI-enabled analytics workflows. • This role blends analytics engineering, automation, and practical AI implementation. • This role works directly on the technical execution of transformation initiatives. • Build Microsoft Fabric pipelines and consolidated Lakehouse models. • Develop certified views with reconciled metric definitions. • Engineer Azure OpenAI prompts for narrative and insight generation. • Build Python-based automation for reporting and compliance workflows. • Support self-service analytics platforms with text-to-SQL and routing logic. • Implement automated compliance and validation checks. • Build signal detection and alerting pipelines. • Track and analyze AI-driven program effectiveness. • Maintain build logs and time tracking aligned to ASC 350-40. • Create Copilot prompt playbooks and best practices. • Monitor pipeline health and resolve data issues. • Support Power BI automation and DAX libraries.