Enterprise Architect (Build) / AI Architect (Build)

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Job Title: Enterprise Architect (Build) / AI Architect (Build)

Location(s): Chicago, IL
(Remote)

Job Summary
The Enterprise AI & Observability Architect is responsible for defining the strategic vision, architecture, governance, and roadmap for enterprise observability, AI-enabled operations, and operational intelligence platforms. This role designs and implements AI-driven solutions that enhance observability, automation, analytics, troubleshooting, and technology decision-making across cloud, hybrid, and on-premise environments.

The architect will establish enterprise architecture standards, lead the adoption of modern observability and AIOps capabilities, and integrate Generative AI, Machine Learning, predictive analytics, and intelligent automation into IT operations. The role works closely with Data Science, Platform Engineering, SRE, Operations, Security, and business stakeholders to improve operational resilience, service reliability, and enterprise technology outcomes.

Key Responsibilities
Enterprise Architecture & Strategy

• Define enterprise-wide strategies for observability, operational intelligence, AI, and AIOps.
• Develop architecture standards, reference architectures, governance frameworks, and technology roadmaps.
• Align observability and AI initiatives with business objectives, cloud transformation, and operational resilience strategies.
• Provide architectural oversight for cloud, hybrid, and on-premise monitoring and observability solutions.
• Evaluate emerging AI, AIOps, observability, and automation technologies and recommend adoption strategies.
• Establish enterprise standards for monitoring, logging, metrics, distributed tracing, service reliability, and operational telemetry.

AI & Machine Learning Architecture

• Define AI/ML architecture standards and reusable reference models.
• Design and implement Generative AI and Machine Learning solutions for IT Operations.
• Develop predictive analytics, anomaly detection, forecasting, and intelligent event-correlation capabilities.
• Leverage Large Language Models (LLMs) to improve operational intelligence, troubleshooting, and knowledge-driven automation.
• Integrate AI services with Dynatrace, observability platforms, enterprise data platforms, and operational systems.
• Design AI and data pipelines supporting scalable, reliable, and production-ready AI solutions.
• Apply MLOps practices for model deployment, monitoring, lifecycle management, and continuous improvement.

Observability & AIOps

• Lead the architecture and adoption of enterprise observability platforms and services.
• Integrate Dynatrace and its Davis AI capabilities with enterprise monitoring, cloud, application, and infrastructure platforms.
• Drive the integration of AI and AIOps capabilities into enterprise IT operations.
• Establish intelligent event correlation, anomaly detection, predictive monitoring, and automated remediation strategies.
• Develop AI-assisted troubleshooting and root cause analysis capabilities.
• Create intelligent operational workflows that improve incident response and reduce manual intervention.
• Promote OpenTelemetry and modern observability practices across applications and infrastructure.

Cloud & Modern Architecture

• Define observability and operational intelligence architectures across Azure, AWS, and GCP.
• Provide architectural guidance for Kubernetes and cloud-native application environments.
• Support observability architectures for microservices, APIs, distributed applications, containers, and modern application platforms.
• Ensure monitoring and telemetry solutions are scalable, resilient, secure, and aligned with enterprise architecture principles.

Governance, Security & Collaboration

• Ensure AI and observability solutions comply with enterprise governance, security, privacy, and responsible/ethical AI standards.
• Establish architectural controls, technology standards, and governance processes for AI-enabled operations.
• Collaborate with Data Science, Platform Engineering, SRE, Cloud Engineering, Security, Operations, and application teams.
• Engage executive and business stakeholders to communicate architecture strategies, technical roadmaps, and investment recommendations.
• Provide technical leadership and mentorship to engineering and architecture teams.

Required Skills

• Enterprise Architecture and architecture governance.
• AI/ML architecture and solution design.
• Large Language Models (LLMs) and Generative AI.
• Predictive analytics and anomaly detection.
• AIOps and AI-driven IT Operations.
• Dynatrace platform architecture and Davis AI capabilities.
• Observability frameworks and OpenTelemetry.
• Cloud platforms: Azure, AWS, and/or GCP.
• Kubernetes and modern cloud-native application architectures.
• Data engineering, AI pipelines, and MLOps.
• Python and commonly used AI/ML frameworks.
• Monitoring, logging, metrics, distributed tracing, and service reliability concepts.
• Executive stakeholder management and cross-functional technical leadership.
• Strong understanding of enterprise security, governance, and responsible AI practices.

Preferred Certifications

• TOGAF
• Dynatrace Certified Professional
• Microsoft Azure Solutions Architect
• Microsoft Azure AI Engineer
• AWS Solutions Architect
• AWS Machine Learning Specialty
• Google Professional Machine Learning Engineer

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.