I'm Ahmed Ali, a software architect and engineering lead. I design and build event-driven backends, web and ecommerce platforms, cloud infrastructure and production AI systems, and lead the teams that ship them.
$ kafka-consumer --topic activity --group activity-workersconsumer group balanced · 3 partitions · lag 0✓ redis dedup 12,481 events 0 duplicates✓ batch writer 100 items / 5s window✓ bullmq classify queued 312 · failed 0✓ cache invalidate dashboards freshp99 write latency 38ms$ 500+
Projects delivered
Web, ecommerce, CMS, ERP and AI platforms
6+
Years engineering
FinTech, AI and SaaS at production scale
100K+
Events per day
Kafka pipelines running in production
20+
Engineers led
Across AI, ecommerce and CMS product lines
From the product your customers use down to the pipelines and infrastructure underneath it, designed, built and taken to production.
The things your customers actually touch, built to hold up once real traffic arrives.
The layer underneath: service boundaries, data flow and the trade-offs written down before the first commit.
AI that ships as a service with failure paths, tracing and evaluation, not a demo that degrades quietly for six months.
Making deployment boring, systems cheaper, and telling you honestly which part is actually the problem.
The four systems clients ask for most often, and the shape each one takes before a single line is written. Yours will differ in the details, but the structure rarely does.
Answers from your own documents, with citations and a real answer when it does not know.
Agents that complete a process by calling real tools, with every step reviewable rather than one opaque generation.
Storefront, checkout and everything behind it, built so a traffic spike is a scaling event, not an outage.
Raw operational events turned into numbers people trust, with dashboards that stay fast as volume grows.
Four platforms, each with a different constraint at its centre: throughput, precision, latency or ambiguity. Every case study walks the architecture and the full pipeline, not the feature list.
These four go deep. Behind them sit 500+ delivered projects, covering ecommerce and CMS platforms, ERP integrations, AI chatbots and agents, automation and internal tools, across client work and products of my own.
See all case studiesSee all case studiesArchitecture is mostly about choosing what happens when something goes wrong. Three rules shape almost everything I build.
Ingestion, processing and delivery each break for their own reasons. An event backbone between them means one slow stage never stalls the rest.
Deduplication keys, idempotency and distributed locks are mechanisms, not hopes. If two replicas can process the same event, something must decide which one counts.
Retries, circuit breakers and dead-letter queues get designed alongside the happy path, because the happy path is not the one that pages you at 3am.
What that has produced
60%+
Lower read latency
Redis cache-first strategy on a FinTech platform
25%
Cloud cost reduction
GCP rightsizing and observability work
~70%
Less deploy effort
Kubernetes and Docker replacing manual releases
50%+
Fewer integration issues
Clear service boundaries and ownership
Chosen per problem rather than per fashion. These are the tools I've taken to production often enough to know their failure modes.
System design · Backend & APIs · Messaging & streaming · AI & agent engineering · Databases · Cloud & DevOps · Frontend & desktop
See the full toolkitMostly the things I wish someone had told me before the incident, not after.
Whether it needs designing from scratch or rescuing from its own success, tell me what you’re building and I’ll tell you how I’d architect it.
Open to remote and hybrid work worldwide