Managed Services AI Platform Architect

AHEAD is a company that builds platforms for digital business, focusing on cloud infrastructure, automation, and analytics. They are seeking a Managed Services AI Platform Architect who will be responsible for designing, building, and scaling AI-powered operational capabilities within the Managed Services organization, with a focus on delivering measurable outcomes and improving service performance.

Responsibilities:

• Design, build, and evolve the Managed Services AI platform — delivering production-grade AI capabilities integrated directly into service delivery workflows
• Lead the development of agentic AI solutions, including incident triage and classification, automated remediation and resolution, knowledge retrieval and summarization, and workflow orchestration and escalation
• Drive use cases from concept through prototype to production, ensuring real operational adoption
• Design and implement agent-based architectures including triage agents, resolution and remediation agents, RAG-based knowledge agents, and orchestration and multi-step workflow agents
• Define patterns for prompt design and structured outputs, tool integration and action execution, memory and state management, and human-in-the-loop controls
• Ensure AI workflows are observable, reliable, and continuously improving
• Architect and integrate AI capabilities across core platforms including ITSM (ServiceNow), monitoring and observability tools, automation frameworks and runbooks, and knowledge management systems
• Embed AI directly into day-to-day operational workflows — not standalone solutions — designed for multi-tenant, scalable managed services environments
• Establish and maintain practical AI architecture standards and reusable patterns based on production usage
• Contribute to the Managed Services AI roadmap, grounded in delivered capabilities and business impact
• Define and enforce guardrails for safe automation: approval workflows and escalation paths, risk boundaries and controls, and observability and auditability
• Align with enterprise architecture standards where appropriate, while prioritizing speed and execution
• Drive measurable improvements across Managed Services operations: incident deflection rates, MTTR reduction, automation and self-healing coverage, ticket volume reduction, analyst and engineer productivity, and service quality and client experience
• Partner closely with Managed Services delivery teams, automation and platform engineering teams, and operations leadership
• Act as a player-coach — combining deep technical contribution with leadership and enablement
• Drive adoption and scaling of AI capabilities across the organization