• Design and implement core Back-End services for real-time bidding, optimization, and ad delivery workflows • Build custom bidding agents for real-time bid decisioning • Develop high-load, low-latency components supporting real-time auction and delivery mechanics • Implement proprietary pacing, bid-shading, and optimization logic to improve campaign efficiency • Design and integrate forecasting capabilities for impressions, reach, outcomes estimation, and campaign planning • Work with OpenRTB, JSON, protobuf, and other ad-tech protocols and data formats • Collaborate with product, engineering, data, and ad operations stakeholders to deliver scalable performance advertising capabilities

• Architecting an AI-first GTM ecosystem that bridges the gap between Sales, RevOps, Marketing, and Customer Success. • Design, code, and deploy custom AI integrations from scratch to connect our CRM, Sales Engagement platforms, and other technology stack components. • Build proprietary internal LLM-based tools to automate account and contact enrichment, outbound messaging for early and middle of the funnel prospects. • Develop agentic workflows that handle routine administrative tasks (e.g., CRM data, meeting summaries, and follow-up scheduling) across the revenue organization. • Partner with RevOps and Marketing Ops to audit the existing tech stack, identifying redundancies where AI can replace high-cost, low-utility third-party vendors. • Implement predictive modeling to identify high-intent pipelines and provide Sales with real-time 'Next Best Action' recommendations. • Ensure data integrity across all platforms, creating a 'single source of truth' that AI models can leverage for accurate forecasting. • Collaborate with Customer Success to build AI-driven retention loops and automated renewal triggers. • Consult with Marketing leadership on AI-driven content distribution and performance marketing automation to lower Customer Acquisition Cost (CAC). • Act as an internal consultant, training GTM teams on how to effectively 'prompt' and utilize deployed AI tools to maximize their individual output.

Role Description As an Application Advisor Intern at Dayforce, you will support innovation projects within the Sales and Solution Advisory organization, focusing on: - Frontend UI/UX design - Customer-facing digital experiences - Conversational interfaces - AI-enabled workflow improvements You will help design, test, document, and improve tools that make information easier to access, understand, and use across customer engagement and sales advisory experiences. Qualifications - Currently pursuing an undergraduate degree in: - Human-Computer Interaction - UX Design - Product Design - Interaction Design - Computer Science - Software Engineering - Information Systems - Business Technology Management - Data Analytics - Business - Commerce - Related field - Strong interest in frontend UI/UX design and customer-facing digital experiences. - Understanding of UX design principles. - Experience creating wireframes, prototypes, journey maps, mockups, or design recommendations. - Familiarity with frontend concepts such as HTML, CSS, JavaScript, TypeScript, React, and APIs. - Strong communication, critical thinking, attention to detail, and collaboration skills. Requirements - Full-time availability of 37.5 – 40 hours weekly is required. - Ability to learn technical concepts related to AI-enabled applications. Benefits - Gain exposure to real-world competitive strategy in a fast-growing HCM technology company. - Develop practical skills in market intelligence, data analytics, and business storytelling. - Contribute to projects with a visible impact on company positioning. - Build skills for a career in software marketing, product development, sales development, or corporate strategy.

• Develop and maintain scalable back-end services. • Design and build the architecture behind the AI systems, developing robust agentic workflows, MCP servers, and scalable integrations between LLMs and our backend infrastructure. • Ensure seamless integration with front-end applications and external services through well-designed RESTful APIs. • Leverage cloud infrastructure (Azure Functions, Azure Storage) for hosting and scaling applications. • Implement security best practices for API authentication (OAuth, JWT) and data protection. • Possibly work on GenAI-driven applications, utilizing AI APIs. • Containerize applications using Docker for environment management.