Program Manager

About AuxoAI AuxoAI helps enterprises transform how they operate by combining business consulting, data, engineering, and Agentic AI. We are building an AI-native consulting model in which every team member is expected to use AI thoughtfully to improve speed, insight, quality, and client outcomes. What You Will Do · Create and maintain the inventory of boundary systems, interfaces, owners, business processes, data objects, and implementation-wave impacts. · Coordinate impact assessments for upstream, downstream, reporting, middleware, third-party, and operational systems connected to Oracle Fusion. · Manage delivery plans for application changes, interface modifications, technical dependencies, testing readiness, deployment, and stabilization. · Track integration design, build, unit testing, SIT, end-to-end testing, UAT support, cutover, and production validation milestones. · Facilitate cross-team dependency reviews across application owners, integration teams, functional teams, data teams, security, infrastructure, and vendors. · Identify hidden downstream impacts caused by changes to data ownership, chart of accounts, master data, file formats, APIs, schedules, or business processes. · Maintain boundary-system RAID items, decisions, action owners, readiness status, and escalation paths. · Prepare leadership reporting on high-risk systems, critical interfaces, unresolved design decisions, and testing or cutover readiness. · Support post-go-live monitoring, defect triage, reconciliation, and stabilization across impacted applications. AI-Enabled Delivery Responsibilities · Use AI to extract systems, interfaces, data flows, decisions, and impacts from architecture diagrams, design documents, meeting notes, and interface specifications. · Apply AI-assisted dependency analysis to identify potentially missed downstream systems and cross-interface risks. · Generate draft impact assessments, test scenarios, readiness summaries, and executive heatmaps from structured tracker data. · Help build a reusable AI-enabled boundary-systems knowledge base and impact-management process. Common AI-First Expectations at AuxoAI Use enterprise AI tools such as ChatGPT Enterprise, Claude Enterprise, Gemini, or equivalent platforms to accelerate delivery and improve decision-making. · Apply AI to automate meeting summaries, action-item tracking, status reporting, executive communications, and document synthesis. · Use AI-assisted analysis to identify delivery risks, cross-team dependencies, emerging bottlenecks, and areas requiring leadership attention. · Continuously identify PMO activities that can be simplified, standardized, or automated through AI and workflow automation. · Validate AI-generated outputs for accuracy, confidentiality, traceability, and business relevance before they are used in program decisions. · Collaborate with consulting, data, engineering, and AI teams to pilot and scale AI-enabled delivery practices across the program. Requirements · 4-6 years of experience in project management, application delivery, systems integration, or enterprise transformation. · Working knowledge of APIs, batch interfaces, file transfers, middleware, application dependencies, and end-to-end testing. · Experience managing cross-team plans, RAID items, dependencies, action tracking, and readiness reporting. · Strong analytical skills and the ability to understand business and technical impacts across multiple systems. · Excellent facilitation, documentation, communication, and stakeholder-management skills. · Comfort using AI tools to analyze complex information and accelerate impact analysis. Preferred Qualifications · Oracle Fusion or Oracle Integration Cloud experience. · Exposure to REST/SOAP APIs, SFTP, middleware, MuleSoft, Informatica, Boomi, or similar integration platforms. · Experience with architecture diagrams, interface inventories, impact assessments, SIT, UAT, or cutover. · Experience with Jira, Azure DevOps, ServiceNow, Smartsheet, Power BI, or Microsoft Project. · Familiarity with enterprise application landscapes in manufacturing, food, consumer products, or supply chain environments. What Success Looks Like · Clear delivery visibility · Early risk identification · Responsible AI adoption · Predictable workstream outcomes