iShare Inc.

QA Automation Engineer

• Build, manage, and evolve shared platform engineering capabilities across Power Platform, Dynamics 365 F&O, Azure, AWS, APIs, integrations, and digital applications
• Support and operationalize AI-enabled development workflows including local agents, Copilot-assisted engineering, orchestration services, and automated SDLC pipelines
• Design and maintain CI/CD pipelines, deployment automation, environment strategies, release controls, and platform governance standards
• Implement reusable platform services, automation frameworks, connectors, templates, shared components, and developer acceleration tooling
• Support AI and automation lifecycle capabilities including Power Platform Copilot Studio, M365 Copilot integrations, Azure AI Foundry, machine learning workflows, and agent orchestration patterns
• Build and support platform observability including telemetry, logging, monitoring, alerting, tracing, and operational dashboards
• Support automated quality engineering practices including pipeline validation, regression execution, automated testing integration, and release gating
• Implement and operationalize platform security controls including RBAC, managed identities, API security, secrets management, DLP policies, audit logging, and environment governance
• Partner with Enterprise Architecture, Cybersecurity, Cloud Engineering, and Data & AI teams to align implementations with enterprise standards and governance requirements
• Support AI governance practices including behavioral monitoring, agent lifecycle controls, Responsible AI enforcement, risk evaluation, and operational review processes
• Assist product and engineering teams with platform onboarding, automation adoption, environment provisioning, troubleshooting, and platform optimization
• Drive platform reliability, resiliency, scalability, and operational excellence across shared engineering services
• Contribute to developer experience improvements through automation, self-service tooling, standardized patterns, and reusable engineering assets
• Support cost optimization, performance tuning, and operational efficiency initiatives across cloud and platform services

Platform Engineer – AI Automation

Consultant

• Assess current P2P processes and identify transformation opportunities.
• Design future-state P2P operating models, policies, and controls.
• Lead process improvements across Requisition-to-PO, Invoice-to-Pay, and Vendor Management.
• Drive automation and digital transformation initiatives (Coupa, Oracle, AI/RPA).
• Analyze P2P KPIs, process bottlenecks, and value-leakage opportunities.
• Support stakeholder management, change management, and user adoption.
• Develop business cases, transformation roadmaps, and implementation plans.
• Ensure compliance with procurement policies, SOX controls, and governance requirements.
• Collaborate with sourcing, procurement, AP, finance, and technology teams.
• Track benefits realization, cost savings, and operational improvements.

P2P Transformation Consultant

General

• Manage and maintain Critical Data Elements (CDEs) and business metadata repositories
• Define, document, and maintain business glossaries and standardized data definitions
• Establish and monitor data quality rules, controls, and validation processes
• Develop and publish data quality dashboards and reports
• Analyze data quality issues and coordinate remediation efforts
• Monitor data quality trends and identify root causes of issues
• Partner with business users to understand data requirements and governance needs
• Support governance forums, working groups, and stewardship activities
• Ensure compliance with enterprise data standards and governance policies
• Assist with regulatory, audit, and compliance reporting requirements

Data Steward

Software Engineer

• Develop and maintain business metadata, technical metadata, data lineage, and Critical Data Element (CDE) frameworks
• Configure and administer metadata management tools (e.g., Collibra), including workflows, domains, and governance processes
• Design and implement metadata ingestion and integration processes across enterprise data platforms
• Integrate metadata platforms with tools such as Databricks Unity Catalog and other data sources
• Build automated metadata synchronization and lineage capture solutions
• Support metadata quality, governance, and stewardship initiatives
• Collaborate with data architects and governance teams to define metadata standards and best practices
• Analyze metadata requirements and implement scalable governance solutions
• Support regulatory, audit, compliance, and risk management initiatives through enhanced data traceability
• Create and maintain technical documentation and governance artifacts

Platform Engineer – AI Automation

P2P Transformation Consultant

Data Steward

Metadata Developer