usman.agent
An AI agent that has read Usman's CVs and engagement history, running on the same patterns he designs for clients. Ask it anything a recruiter would ask.
- grounded
- Answers only from documented engagements.
- human fallback
- Anything it can't answer, it offers to pass straight to Usman.
Hire one head, get three roles.
AI initiatives normally require an architect to design, an analyst to de-risk, and a developer to deliver. I operate fluidly across all three — no hand-off losses, no translation gaps, one accountable owner from whiteboard to production.
AI Solutions Architect
End-to-end solution design where the model is one component of a larger system.
- LLM & agent system design — tools, loops, guardrails, failure modes
- Model strategy: hosted vs. self-hosted, cost, privacy, latency
- Ontology & knowledge architecture for grounded reasoning
- Integration with identity, networking & enterprise systems
"What should we build, and on what foundation?"
AI Solutions Analyst
Turning AI ambition into an executable, defensible roadmap before money is spent.
- Use-case discovery and value mapping across business functions
- Build-vs-buy and platform evaluations, free of vendor hype
- Readiness assessment: data, infrastructure, security, teams
- Cost, risk & governance analysis for AI adoption
"Which AI investments will actually pay off?"
AI Solutions Developer
Hands-on delivery of AI-powered applications with production discipline.
- LLM-powered applications across web & enterprise stacks
- Tool-calling agents for narrow, well-scoped tasks — human in the loop
- MCP & context engineering: models pull what they need
- CI/CD, GitOps & observability for AI workloads
"Can we have it working, shipped, and monitored?"
assess → architect → build → operate → evolve — one accountable owner, end to end
Expertise Domains
AI-first positioning, backed by a decade of full-stack engineering. Each domain is production experience, not a course certificate.
AI & Agent Architecture
How agent systems are put together — LLM loops, tool orchestration, control flow and where they break — with hands-on builds at a focused scale rather than sprawling autonomy. Self-hosted and private AI stacks, local inference, and MCP integrations for context-efficient, privacy-first systems.
Ontology & Knowledge Engineering
Structuring domain knowledge — entities, relationships, tool semantics — so AI reasons over meaning instead of drowning in raw text. Context engineering as an architectural discipline.
Solution & Cloud Architecture
Enterprise Azure end to end: multi-tenant SaaS, network topology, identity-first security, governance, API gateways, DevSecOps supply chain.
Platform Engineering & DevOps
Kubernetes at production scale, GitOps delivery, IaC, and CI/CD engineered as products — with security gates built into every pipeline.
.NET & Enterprise Software
The full .NET lineage — WebForms to modern .NET Core — including modernization into cloud-native SaaS. Real-time with SignalR, PostgreSQL, SQL Server.
AI-Accelerated UI Engineering
Next.js and React on Tailwind, shadcn/ui and Flowbite — AI-assisted velocity with human-owned architecture, accessibility, and polish.
SRE, Data & Observability
SRE as a led discipline — SLAs, ITIL incidents, structured RCA — on Kafka event streams, lakehouse stacks, and full-depth observability.
Cloud Migration & Portability
Moving workloads between clouds — and off them — without breaking the business. Architectures designed for exit from day one.
The stack, hands-on.
Tools used across engagements, grouped by where they sit in the system.
cloud · platform · delivery
- Microsoft Azure
- Kubernetes / AKS
- Docker
- Helm
- Terraform
- Bicep
- ArgoCD
- Azure DevOps
- Jenkins
- GitHub Actions
- Kustomize
- Ansible
- Istio
- Kong
- NGINX Ingress
- cert-manager
- Harbor
- Coolify
- CapRover
- Cloudflare
ai · data · application
- LLM APIs
- Ollama · Local Models
- Model Context Protocol
- RAG & Ontology
- Qdrant
- Azure AI Foundry
- .NET Core
- Next.js
- React
- Tailwind CSS
- SignalR
- Kafka
- Debezium
- PostgreSQL
- Redis
- Spark
- Iceberg
- MLflow
- Grafana
- Prometheus
- Loki
- OpenTelemetry
- Key Vault
- Keycloak
- Trivy
- Gitleaks
- Cosign
Selected Engagements
Delivered for enterprise clients across industries. Client identities withheld under confidentiality — the architecture speaks for itself.
AI Sales & Marketing Automation Platform
Multi-tenant, AI-driven SaaS orchestrating automated sales engagement. Designed Kubernetes infrastructure for scalable AI microservices, multi-environment CI/CD, Kafka event streaming, and identity-secured delivery.
AI Clinical Imaging & Research Platform
Clinical platform for ocular image analysis and trial workflows. Multi-environment Kubernetes with ten+ HA microservices, GitOps delivery, centralized observability, structured RCA.
IoT Asset Monitoring Platform
Real-time monitoring of logistics and industrial assets. Kafka telemetry ingestion stable at streaming scale, automated deployments, and fleet-health dashboards.
Logistics Release & Deployment Platform
Cloud asset tracking and workflow management. Owned release engineering across Azure — automated build and release, containerized delivery, reduced deployment downtime.
Operating Principles
The judgment layer that a decade in production buys you.
Let's take your AI from ambition to production.
Available for AI solution architecture, advisory, and delivery engagements — full-time leadership roles or focused consulting. One conversation is enough to know if I can help.