Work
Selected engagements demonstrating multi-disciplinary engineering across infrastructure, backend systems, and data platforms.
Government Infrastructure Modernization
Problem
Multi-cluster Kubernetes estate suffering deployment failures and operational risk. Critical services unreliable due to 8,000+ lines of brittle bash/Jenkins logic. Manual processes blocking release velocity. Compliance requirements for government security standards.
Approach
Replaced fragile bash/Jenkins workflows with robust Terraform-based GitHub CI/CD. Implemented algorithm-driven infrastructure modules for automated configuration. Integrated AWS Secrets Manager with external-secrets operator for compliance. Eliminated environment drift and security gaps through infrastructure-as-code.
Outcome
Reduced onboarding time and compliance risk significantly. Cut release delays and stability issues. Increased reliability of critical services by modernizing multi-cluster Kubernetes estate. Reduced deployment failure and operational risk through automated, compliant infrastructure.
Mission-Critical Telemetry Migration
Problem
Mission-critical embedded QNX telemetry system processing 4,000+ high-frequency CAN messages per second required cloud migration. On-premises infrastructure created single point of failure for live race broadcasts. Race-day failure risk unacceptable. Needed proof of cloud-native architecture feasibility.
Approach
Delivered proof-of-concept migration to AWS, validating cloud-native telemetry pipelines for broadcast data. Designed high-throughput ingestion architecture ensuring millisecond-level message processing. Demonstrated future-proofed infrastructure with lower operational risk and dependency. Enabled collaboration across embedded, DevOps, and software teams to meet tight race-season timelines.
Outcome
Proved scalability with high-throughput ingestion architecture in AWS. Reduced race-day failure risk by validating cloud-native telemetry pipelines. Enabled long-term resilience by demonstrating feasibility for full migration. Proved real-time processing of 4,000+ messages per second powering fan-facing features.
Supply Chain Intelligence Platform
Problem
SaaS platform requiring multi-tenant infrastructure. Complex data models for supply chain analytics. Frontend, backend, and infrastructure all needing coordinated development.
Approach
Full-stack development from infrastructure to UI. AWS architecture with multi-tenant isolation. Backend services for supply chain data processing. React frontend for analytics visualization. Three-tier Terraform for rapid environment provisioning.
Outcome
Production SaaS platform with secure multi-tenant architecture. Full-stack solution delivered without coordination overhead. Infrastructure-as-code enabling new environments in minutes rather than weeks.
Cloud IoT SaaS Platform
Problem
Industrial technology company needed market entry for embedded analytics SaaS. Required transition from on-chip analytics to scalable cloud platform—enabling remote management for devices without physical cabling dependency. Needed proof-of-concept to secure board-level funding.
Approach
Delivered proof-of-concept Cloud IoT platform demonstrating end-to-end IoT analytics on cloud-native stack. Proved technical feasibility with live demo to board-level executives. Demonstrated high performance with RESTful backend and time-series database ingesting terabytes per second. Provided cross-functional technical leadership across frontend, backend, and data architecture.
Outcome
Secured SaaS market entry for client by delivering project as scalable cloud delivery model. Secured post-PoC funding following successful board-level presentation. Demonstrated cohesive delivery across frontend, backend, and data architecture ensuring technical feasibility.
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