Principal AI Architect

ALKEME Insurance · Full-time Aug 2025 – Present · 1 month California, United States · Hybrid

I lead the design and implementation of scalable, automated, and AI-driven solutions across complex cloud environments. My work bridges AI architecture, automation engineering, and full-stack development, enabling high-performance systems that deliver real-time insights and seamless operational efficiency.

Key Responsibilities & Impact

• Architect and maintain end-to-end microservices for mission-critical, cloud-native applications and AI-driven automation.
• Lead development of CI/CD pipelines to streamline deployment, testing, and monitoring, ensuring rapid and reliable releases.
• Automate infrastructure provisioning ensuring scalability, performance, reliability, security and cost efficiency.
• Design and maintain automated testing frameworks for mobile, web, and backend systems.
• Build AI-enhanced data pipelines to process high-volume data with real-time analytics and reporting.
• Oversee cloud resource optimization across AWS, GCP, and Azure, automating compute, storage, and networking operations.
• Collaborate with executive suite, share-holders, and cross-functional teams to automate ingestion and processing of large-scale datasets for AI model training and inference.
• Implement dependency-aware testing systems and continuous integration strategies to maximize production reliability.

Additional Expertise

• AI-based automation and image processing for intelligent content management.
• Mobile application testing and automation (iOS & Android).
• Machine learning solutions for predictive analytics and automated decision-making.

Engineering Stack Vision (Proposal)

This section outlines a high-level engineering stack vision for a greenfield rollout with Kubernetes as the runtime and Azure as the cloud provider, balancing developer freedom and velocity with sensible security and operations readiness.

Goal: To deliver a modern, fast, secure, scalable, auditable, developer-friendly platform for building and operating containerized applications using Kubernetes. Provide standardized CI/CD pipelines to support rapid innovation. Minimize manual work, reduce human error, and increase development velocity with automation and infrastructure-as-code, centralize secrets & key management. Provide visibility into every layer of infrastructure and code with observability and feedback loops. Provide operational resilience via backup, disaster recovery, and helpdesk support. Support experimentation and flexibility without compromising safety by embedding security into every stage with layered security and compliance-ready processes.

High-Level Components:

• Source Control: Git-centric workflows with branch protection and PR gates.
• CI Orchestration: Jenkins for builds/tests.
• Continuous Code Scanning: CodeQL to identify vulnerabilities and bugs.
• Infrastructure as Code (IaC): Terraform to create a hub-and-spoke architecture.
• Secrets Management: Azure Key Vault as the single source of secrets.
• Access Control: Policy-driven and role-based access within Azure Active Directory.
• Observability: Prometheus and Grafana for monitoring.
• Log Management: ELK and Azure Monitor for log analysis.
• Early Alerting: SLO (Service Level Objective) implementation.

This framework lays the foundation for a secure, scalable environment, balancing speed with guardrails and resilience for enterprise-grade reliability. Adopting this framework ensures every commit and deployment is backed by the best tooling, security, and practices to enable rapid delivery.