AI Architect

AI Architect | Enterprise Architecture | Policy-as-Code | GenAI Enablement

Seasoned AI Architect with 12+ years of experience designing and delivering scalable enterprise platforms with a strong focus on AI/ML integration, Policy-as-Code governance, and cloud-native automation. Proven expertise architecting knowledge graphs, GenAI-powered remediation engines, and drift detection pipelines for Fortune 500 environments. Adept at translating enterprise architecture standards (TOGAF, SAFe, DDD) into actionable, machine-enforced policies using OPA/Rego and integrating with CI/CD, IaC, and Observability ecosystems (GitHub Actions, ArgoCD, Terraform, Kubernetes, OpenTelemetry, Grafana). Skilled in leading cross-functional teams to deliver robust event-driven architectures and continuous learning frameworks utilizing Python, Go, and TypeScript. Excels at stakeholder engagement, technical evangelism, and mentoring teams on AI-enabled governance, architecture conformance, and cloud compliance. Passionate about driving innovation at the intersection of AI, platform engineering, and DevSecOps.

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Key Skills:
- AI Knowledge Graphs, GenAI, LLMs, RAG
- Policy-as-Code: OPA/Rego, Conftest, Kyverno
- CI/CD, IaC: GitHub/GitLab, Jenkins, ArgoCD, Terraform, Kubernetes
- Observability: OpenTelemetry, Prometheus, Grafana, Elastic Stack
- Event-Driven Architectures: Kafka, Pub/Sub
- Enterprise Architecture: TOGAF, C4, DDD
- Cloud & Containers: Azure, AWS, Kubernetes, Docker, OpenShift
- Programming: Python (expert), Go, TypeScript

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Sample Professional Experience Bullet Points (for your resume):

- Defined and implemented enterprise-wide AI architecture strategy, including knowledge base and GenAI-powered remediation engine, integrated with CI/CD and observability platforms.
- Led cross-team delivery of Policy-as-Code enforcement using OPA/Rego, automating architectural governance, drift detection, and compliance reporting.
- Architected continuous learning pipelines for risk scoring and anomaly detection leveraging telemetry analytics and historical drift patterns.
- Oversaw development of microservices-based event bus and API layers for scalable, resilient platform integration.
- Evangelized "AI-enabled architecture governance" to C-level stakeholders, delivering roadmaps, maturity models, and actionable insights.
- Mentored architects and engineers on architecture observability, drift prevention, and AI/ML workflow best practices.

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Certifications:
- TOGAF Certified (optional if applicable)
- Azure/AWS Solution Architect (optional if applicable)
- OPA/Policy-as-Code Practitioner (if you have this)