Senior AI Architect — AIOps & Enterprise Platform Lead

NATIONMIND LLC

Pittsburgh (Allegheny County)

On-site

USD 135,000 - 180,000

Part time

14 days+

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Job summary

NationMind LLC in Pittsburgh, PA is seeking an experienced AI Architect to lead the design and implementation of AI-enabled AMS and AIOps platforms, shaping enterprise AI architecture and governance. You will drive data contracts, telemetry schemas, and policy controls while coordinating with ITSM, CI/CD, and cloud ecosystems to improve operational efficiency and business outcomes.

Ideal candidates bring 10+ years in enterprise architecture, 5+ years in AI/ML, and deep knowledge of ServiceNow,

Qualifications

Bachelor's or Master's degree in CS, IT, AI, or related field.
10+ years in enterprise architecture, cloud, IT ops, or software engineering.
5+ years in AI/ML, AIOps, or automation architecture.
Strong knowledge of ServiceNow, Jira, CMDB, CI/CD, cloud platforms, and observability tools.
Experience with LLMs, AI agents, orchestration frameworks, and governance.

Responsibilities

Define and implement the target architecture for AI-enabled AMS, including telemetry ingestion, unified observability (metrics, logs, traces), event correlation, and signal-driven operations.
Design a vendor-agnostic AI agent orchestration layer to coordinate AIOps platforms, LLM agents, runbooks, automation tools, and ITSM workflows.
Develop scalable and resilient AI architectures across cloud, on-premises, edge, and hybrid environments.
Establish integration patterns with ITSM platforms such as ServiceNow and Jira, collaboration tools, CMDBs, CI/CD pipelines, and cloud monitoring solutions.
Drive automation strategies for incident management, root cause analysis, remediation, and service operations.
Create and maintain data contracts and normalized telemetry schemas across applications, infrastructure, cloud, and edge environments.
Ensure data lineage, quality, consistency, and governance to support AI and analytics initiatives.
Define policies for data retention, encryption, privacy, access controls, auditability, and regulatory compliance.
Implement Responsible AI frameworks and governance controls.
Establish policy validation, bias testing, red-team exercises, safety filters, and human-in-the-loop approval mechanisms for critical AI-driven actions.
Ensure AI solutions comply with organizational, legal, and ethical requirements.
Define and evolve emerging AI operations roles, including AI Ops Engineer, Agent Supervisor, Prompt/Runbook Engineer, and Reliability Engineer.
Collaborate with executive leadership, engineering teams, operations teams, and business stakeholders to align AI initiatives with strategic goals.
Evaluate emerging AI technologies and recommend adoption strategies.