Architecting Scalable SaaS & AI Platforms
I work with founders, CTOs, and engineering teams to design cloud-native, API-driven, and AI-enabled platforms that scale reliably and sustainably.
My focus is not ticket execution. It is architecture, governance, and long-term technical leverage.
Who I Work With
SaaS founders building scalable products
AI startups integrating LLM capabilities
Engineering teams modernizing infrastructure
Companies evolving API platforms
Investors requiring technical due diligence
If your system depends on Kubernetes, APIs, distributed systems, or AI infrastructure — we speak the same language.
Core Capabilities
Fractional CTO
Strategic technical leadership without full-time overhead.
- Architecture direction and technical roadmap
- AI strategy and integration planning
- Infrastructure maturity and operating model design
- Technical hiring guidance and engineering process alignment
- Cloud cost optimization and scalability planning
You may need this when:
- — Your architecture is evolving faster than your roadmap
- — You are preparing for funding or scaling
- — You need senior-level technical guidance
- — Infrastructure costs are growing unpredictably
API Platform Architecture & Management
Designing APIs as governed product infrastructure.
- API Gateway architecture (APIM, Gateway API)
- API lifecycle management (versioning, deprecation, compatibility)
- Security boundary design (OAuth2, OIDC, mTLS, zero-trust)
- Policy enforcement (rate limiting, quotas, throttling)
- Observability & SLA governance (metrics, tracing, usage analytics)
- Multi-tenant and multi-cluster API exposure strategy
You may need this when:
- — API versions are difficult to control
- — Your gateway layer is becoming a bottleneck
- — Security boundaries between internal and external APIs are unclear
- — You are migrating from legacy API management to cloud-native gateway architecture
AI Systems Architecture
AI as infrastructure — not an experiment.
- LLM integration architecture for SaaS platforms
- AI agent systems and orchestration design
- Cost-aware inference and token governance strategies
- Secure AI API exposure and abuse prevention
- AI observability (latency, quality, cost tracking)
- Structured AI capability layering within product architecture
You may need this when:
- — AI features feel bolted onto your product
- — LLM costs are rising without control
- — There is no governance around AI API usage
- — You want to build AI agents into your SaaS platform
Kubernetes & Cloud-Native Platform Architecture
Production-grade infrastructure built for scale.
- Kubernetes platform architecture (AKS, on-prem, hybrid, multi-cloud)
- GitOps delivery with Argo CD and environment isolation
- Service mesh integration (Istio) and traffic control design
- Ingress to Gateway API modernization strategy
- Observability stack integration (metrics, logs, tracing)
- Secure multi-tenant SaaS infrastructure patterns
You may need this when:
- — Your clusters feel fragile or difficult to evolve
- — Multi-environment deployments are inconsistent
- — Ingress and gateway policies are hard to manage
- — You are preparing for multi-cluster or multi-tenant growth
Let’s Talk
If you're building a serious SaaS or AI product and want architecture that scales with ambition — let’s discuss your system.
Schedule a Strategy Call