**Key Responsibilities include:** - Managing target segment configurations, overseeing data integrity - Partnering with the Senior Lifecycle Marketing Manager to develop and launch engaging email sequences, nurture campaigns, and triggered communications. - Working closely with Revenue Operations and the Marketing Technology team, the Marketing AI and Automations Lead turns complex marketing challenges into effective, scalable technical solutions. - Combining expert platform knowledge with cutting-edge strategic vision, this role stands as the organization's trusted authority on marketing automation and AI innovation.

• Support, design, build, manage, and configure solutions within customers’ managed platforms or services under SHI’s management. • Collaborate with internal teams, customers, and partners on projects and service improvement initiatives. • Monitor and optimize environments for optimal system performance. • Engage directly with customers through status updates, change requests, meetings, incident responses, and projects. • Track time and document work in SHI’s PSA system, submitting weekly timesheets. • Provide assistance to lower tiers when needed based on resource constraints. • Mentor and train lower tier engineering employees and service desk employees.

• Integrate Agentforce with the existing Coveo chatbot as an intelligence layer (conversational AI) (without replacing it). • Build AI support agents including **Case Viewer, Case Status, Escalate Case and Case Comment agents **to enable end-to-end case management in chat. • Connect agents to Salesforce using Flows/APIs to retrieve cases, fetch updates, and post comments. • Develop AI features such as **case summarization, suggested replies, and recommended knowledge articles**. • Create dashboards to analyze case trends, identify recurring issues, and flag high-risk accounts.****Lead the capstone project **to design and deliver an AI-powered support experience showcasing real business impact. • Explore indexing video transcripts so academy videos are surfaced based on their actual content, not just course descriptions.

• Own the end-to-end operationalization of ML and AI solutions—from development to scalable, reliable production systemsthat integrate seamlessly with other digital tools. • Design, automate, and maintain CI/CD pipelines for model training, testing, deployment, and retraining (Azure DevOps, Databricks). • Build, optimize, and version model lifecycle workflows, ensuring reproducibility, lineage, and governance across the ML/AI platform. • Monitor production models for performance, drift, reliability, and resource usage; implement automated retraining workflows. • Optimize compute, storage, and orchestration across the Databricks platform to ensure efficient, cost-effective operations. • Collaborate closely with ML/AI Scientists, Data Engineers, and DWH team to transform research-grade models into production-ready services. • Contribute to advancing our ML/AI platform, tooling, automation standards, and best practices.