AI Architect -W2 only

Nationmind•Pittsburgh, PA

23h•Onsite

About The Position

We are seeking an experienced AI Architect to lead the design and implementation of next-generation AI-enabled Application Management Services (AMS) and AIOps platforms. The ideal candidate will define enterprise AI architecture, establish data and governance frameworks, and drive the integration of AI, automation, observability, and ITSM ecosystems to improve operational efficiency and business outcomes.

Requirements

Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field.
10+ years of experience in enterprise architecture, cloud platforms, IT operations, or software engineering.
5+ years of experience in AI/ML, AIOps, observability, or automation architecture.
Strong understanding of ServiceNow, Jira, CMDB, CI/CD, cloud platforms (AWS, Azure, GCP), and observability tools.
Experience with LLMs, AI agents, orchestration frameworks, and enterprise AI governance.
Knowledge of data governance, cybersecurity, privacy regulations, and Responsible AI principles.
Excellent stakeholder management, communication, and leadership skills.

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.
Enable seamless interoperability between AI services, operational platforms, and enterprise applications.
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.