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