// Cloud · AI · Data Architecture
15+ years delivering cloud, data, and AI systems for regulated industries. Experienced in large scale cloud migrations, distributed APIs, low‑latency data pipelines, data lakes, semantic and lexical search, and LLM‑driven data intelligence. Focused on building secure, scalable, production‑ready platforms that turn complex data into measurable outcomes.
What I do
Engineer the entire data and AI stack, from ingestion pipelines to intelligent systems, anchored in architecture that scales reliably in production.
Architect and deliver hybrid and multi‑cloud environments on AWS and Azure, supporting everything from new cloud foundations to high‑stakes migrations. Security is embedded throughout the stack, and every engagement is optimized for cost, scale, and compliance.
Build hardened, production‑ready REST APIs and microservice architectures using Spring Boot, with clean contracts, resilient patterns, and security baked in from the start.
Automated infrastructure and deployment pipelines across AWS, Azure, GCP and IBM, ensuring predictable releases and operational confidence.
Providing technical leadership, team mentorship, and architectural direction across major enterprise transformations in banking, retail, and telecom.
Career
Over 15 years consulting to large enterprises across banking, financial services, retail, telecommunications, and the public sector, I have helped organisations move faster, operate more securely, and unlock the value trapped in their data. My engagements have consistently translated into tangible outcomes: cloud migrations that eliminated costly on-premises infrastructure while hardening security posture; microservice platforms that enabled product teams to ship independently and at pace; and data pipelines that turned fragmented, siloed records into real-time, queryable assets that the business could actually act on. I have stepped into programmes where the architecture was at risk and stabilised them — establishing the cloud infrastructure foundations, security models, and engineering practices that allowed cross-functional squads to deliver with confidence. More recently I have helped clients move beyond conventional data management into AI-powered capabilities: building intelligent document search systems that make vast unstructured archives instantly discoverable, and real-time data replication pipelines that keep distributed systems in sync for analytics and downstream AI workloads. The consistent measure of success across every engagement has been whether the client's team is stronger, their systems more resilient, and their organisation better positioned long after the work is done.
Writing
APRIL 2026
How to tackle meaning-based search across large organisational document repositories using local LLMs and vector embeddings.
Read article → Data · StreamingJULY 2025
A practical walkthrough of implementing real-time data sync across distributed systems — essential for analytics and AI pipelines.
Read article →JUNE 2019
Encrypting cluster traffic for open-source Hazelcast where native TLS support isn't available — a practical security pattern.
Read article →APRIL 2017
Understanding the surprising interaction between Docker's networking and host-level iptables firewall rules.
Read article →OCTOBER 2016
Using MongoDB's atomic operators ($inc, $set, $unset) with Spring Data for safe concurrent counter and field updates.
Read article →ALL POSTS
Cloud architecture, AI & data pipelines, distributed systems, security, and open source.
Open Source
Open source contributions published under business-friendly licences — most available at github.com/kamranzafar.
A configurable dynamic class loader for loading Java classes from JARs and directories at runtime, with Spring integration.
Lightweight Java utility libraries published to Maven Central.
A selection of mobile applications available on the Play Store.
Working code for every technical post — Kafka/CDC pipelines, OpenSearch vector search, Docker, Spring Boot, and more.
// Let's talk
Whether it's cloud architecture, an AI or data pipeline project, or a consulting engagement — I'd love to hear from you.