AI Engineer

Job Description

The AI Engineer is a key member of IT@IFS Global IT Support, responsible for designing, building, and maintaining AI-powered agents and automation solutions that enhance service delivery across the Service Desk, Major Incident Management, Problem Management, and Escalation Management, asset management, local IT support functions. This role focuses on building intelligent AI agents and automated workflows using enterprise AI agent and automation platforms including conversational agents, autonomous agents, and business process automation, all integrated with existing platforms, data sources, and enterprise services to improve operational efficiency and end-user experience.

The AI Engineer works closely with IT Support leadership, Subject Matter Experts (SMEs), Enterprise Service management team, AI Team and product teams to translate operational requirements into working AI-enabled agents and automations. This includes configuring conversational agents, autonomous agents, and decision-support experiences grounded in enterprise knowledge sources, integrating with enterprise applications and data via standard and custom connectors, and ensuring all AI outputs and automations meet quality, accuracy, and reliability standards.

Key Responsibilities of AI Engineer

AI Solution Development

• Design and develop AI-driven features such as conversational agents, recommendation systems, and intelligent automation workflows for IT support. 
• Implement AI solutions using modern frameworks, APIs, and cloud AI services. 
• Translate business and technical requirements into working AI-enabled agents and automations.

Testing & Quality Assurance

• Test, debug, and validate Copilot Studio agents and Power Automate flows, etc.
• Identify and resolve issues such as hallucinations, response inconsistencies, misrouted topics, and flow/connector failures.
• Ensure AI outputs and automations meet quality, accuracy, and reliability standards.

Integration & Connectors

• Integrate agents and flows with enterprise applications and data using standard and custom connectors.
• Connect agents to knowledge sources (SharePoint, Dataverse, websites, documents) and back-end systems via APIs and custom connectors.
• Implement secure connectivity between agents, flows, and enterprise services.

Documentation & Knowledge Management

• Create technical documentation for agents and automations, including topic/flow diagrams and integration instructions.
• Maintain solution documentation and author/maker guides.

Collaboration & Stakeholder Engagement

• Work with product teams, engineers, and consultants to deliver AI capabilities aligned with business requirements.
• Participate in agile ceremonies and contribute to solution discussions.

Continuous Learning & Innovation

• Stay up to date with developments in AI technologies, tools, and frameworks. 

• Experiment with emerging models and libraries.