AI Delivery Technical Lead

Position Summary

We are seeking a highly motivated and experienced Technical Lead, AI Delivery to join our Corporate Applications AI Solution Delivery Team. This role will lead the design, development, implementation, and operationalization of enterprise AI solutions across Finance, Supply Chain, Procurement, HR, and Shared Services platforms.

The successful candidate will possess deep expertise in Oracle AI Agent Studio, Oracle Fusion Cloud Applications, AI architecture, GenAI technologies, and enterprise integration patterns. This individual will work closely with business stakeholders, solution architects, vendors, security teams, and delivery teams to transform AI opportunities into scalable production solutions that drive business value.

Key Responsibilities

AI Solution Leadership

• Lead the technical design and delivery of AI-enabled solutions across Oracle ERP, HCM, SCM, and Procurement platforms.
• Design, configure, test, and deploy Oracle AI Agents using Oracle AI Agent Studio.
• Evaluate, recommend, and implement Oracle-delivered AI Agents and custom AI agent solutions.
• Establish technical standards and best practices for AI solution development and deployment.
• Drive the design of agentic workflows, AI orchestration, and business process automation solutions.

Oracle AI Agent Studio

• Configure and manage Oracle AI Agent Studio environments.
• Design and develop custom AI agents and agent teams.
• Configure agent tools, knowledge repositories, workflows, roles, and security.
• Integrate AI agents with Oracle Fusion APIs, business objects, and enterprise systems.
• Optimize agent performance, monitoring, evaluation, and lifecycle management.
• Support AI solution scaling from Proof of Concept (POC) through enterprise production deployment.

Architecture & Integration

• Define end-to-end AI solution architectures.
• Design integrations between Oracle Fusion, Microsoft 365, SharePoint, Teams, Azure AI services, and other enterprise platforms.
• Ensure solutions adhere to enterprise architecture standards, cybersecurity requirements, and governance frameworks.
• Review technical designs and provide guidance to development teams and vendors.

Delivery Leadership

• Lead technical workstreams through discovery and solution design
• Collaborate with the Corp Apps Delivery and QE Teams for development, testing, deployment, and Hypercare activities.
• Collaborate with Program Managers and Product Owners to estimate effort, manage technical risks, and deliver against committed timelines.
• Mentor developers, analysts, and technical consultants.
• Support vendor selection, solution reviews, and technical quality assurance.

Governance, Security & Compliance

• Ensure compliance with AI governance, privacy, security, and responsible AI requirements.
• Partner with Cyber Security, Risk Management, QE, and Architecture teams.
• Develop governance controls, technical documentation, and operational support models.
• Support AI risk assessments and production readiness reviews.

Innovation & Strategy

• Identify opportunities to leverage AI capabilities to improve productivity, automation, customer experience, and operational efficiency.
• Evaluate emerging AI technologies and Oracle AI roadmap enhancements.
• Support the Corporate IT AI Strategy and AI intake process.
• Contribute to AI Centre of Excellence practices, standards, and reusable assets.

Required Qualifications

Education

• Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline.
• Master's degree considered an asset.

Experience

• 8+ years of enterprise application delivery experience.
• 5+ years in solution architecture, technical lead, or senior development roles.
• 3+ years delivering AI, ML, GenAI, or intelligent automation solutions.
• Experience delivering large-scale enterprise transformation initiatives.

Technical Skills

Mandatory

• Oracle Fusion Cloud Applications (ERP, SCM, Procurement, HCM).
• Oracle AI Agent Studio.
• Oracle Fusion APIs and integration framework.
• REST APIs and enterprise integration patterns.
• AI/GenAI technologies and LLM concepts.
• Infrastructure, identity management, and role-based security models.
• SDLC, Agile, DevOps, and Quality Engineering practices.