Managed Services AI Platform Architect
New
Based in the United StatesFull-TimeSenior
SalaryCompetitive annual compensation with On-Target Earnings (OTE) in the range of $225,000–$250,000 USD
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Job Details
- Required Skills
- Artificial IntelligenceServiceNow
Requirements
- Proven experience designing and delivering AI/LLM-based systems, including agentic AI, RAG pipelines, and orchestration frameworks.
- Strong background in IT operations, managed services, or enterprise service delivery environments with a focus on automation and workflow optimization.
- Hands-on experience integrating with ITSM platforms such as ServiceNow, as well as observability and monitoring tools.
- Deep understanding of cloud-native architectures and scalable system design for production environments.
- Ability to translate operational and service delivery challenges into AI-driven technical solutions with measurable business outcomes.
- Experience building or deploying AI agents, AIOps solutions, or self-healing systems in production settings.
- Familiarity with multi-tenant architectures and enterprise-grade managed services platforms.
- Strong execution mindset with ability to move from concept to production quickly and effectively.
- Excellent communication skills with the ability to influence technical and operational stakeholders.
Responsibilities
- Design, build, and scale a production-grade AI platform for managed services, embedding AI capabilities directly into operational workflows.
- Lead development of agentic AI systems including incident triage, classification, automated remediation, knowledge retrieval, and multi-step workflow orchestration.
- Architect RAG-based systems, AI agents, and orchestration frameworks with strong emphasis on reliability, observability, and continuous improvement.
- Integrate AI capabilities with ITSM platforms (e.g., ServiceNow), monitoring tools, automation engines, and knowledge management systems.
- Define and enforce AI architecture standards, reusable patterns, and operational guardrails including escalation paths and human-in-the-loop controls.
- Contribute to the AI roadmap based on delivered capabilities, focusing on measurable operational impact.
- Drive key outcomes such as incident deflection, MTTR reduction, automation coverage, and improved service quality.
- Partner closely with delivery, engineering, and operations teams while acting as a player-coach combining hands-on building with technical leadership.
- Lead adoption and scaling of AI-powered workflows across managed services environments.
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