// Solutions Architecture · Cloud · AI
16+ years designing microservices, event-driven and cloud-native platforms for regulated enterprises in banking, retail, telecommunications and the public sector. From API and integration platforms and cloud modernisation to generative and agentic AI, RAG and vector search, I build secure, compliant, production‑ready systems, and lead the teams that deliver them.
What I do
Establish the architectural foundations for enterprise platforms: hardened APIs, integration and middleware, and microservice and event‑driven architectures built on Spring Boot and Kafka, with reusable patterns and architecture governance that teams can build on for years.
Take generative and agentic AI into production: LLM integration with Anthropic, OpenAI and Ollama, retrieval‑augmented generation over vector search, MCP tools and servers, and prompt and context engineering. And bring AI into the engineering process itself, across the SDLC, with an eye on token cost.
Architect and deliver hybrid and multi‑cloud environments on AWS, Azure and GCP, supporting everything from new cloud foundations to high‑stakes migrations. Every engagement is built on secure foundations and optimised for cost, scale, reliability and compliance.
Real‑time replication, CDC and streaming pipelines, ETL/ELT and data lakes across relational, NoSQL and vector stores, keeping distributed systems in sync for analytics and AI workloads.
Security by design for regulated environments: identity, encryption and policy enforced at every layer, aligned with ISM and OWASP, and built to pass the audit as well as the attack.
Secure, automated infrastructure and delivery pipelines across AWS, Azure and GCP, with platform standards and observability that make releases predictable and production calm.
Providing technical leadership, team mentorship, and architectural direction across major enterprise transformations in banking, retail, telecommunications and the public sector.
Career
Over 16 years I have worked with large enterprises in banking, financial services, retail, telecommunications and the public sector, helping them move faster, operate more securely, and unlock the value in their data. That has meant cloud migrations that retired costly on‑premises infrastructure while hardening security, microservice and event‑driven platforms that let product teams ship independently, and data pipelines that turned siloed records into real‑time assets the business could act on. I have stepped into programmes where the architecture was at risk and stabilised them, establishing the cloud foundations, security models and engineering practices that let cross‑functional squads deliver with confidence. More recently I have helped teams move into AI‑powered capabilities: intelligent document search, agentic workflows, and real‑time replication feeding analytics and AI workloads. The measure of success has always been whether the client's team is stronger, and their systems more resilient, long after the work is done.
Live Projects
quranai.au ↗
Ask a question and get a cited, verified answer from the Qur’an, tafsir, and hadith — Sunni and Shia sources, balanced side by side. The model answers only from retrieved sources, each checked against the original text.
Livelucidflow.com.au ↗
Your notes, already organised. Capture raw thoughts by text or voice and AI sorts them into tasks, decisions, risks, and follow-ups — with team collaboration, Jira integration, and progress reporting.
Open Sourcehalyx.dev ↗
One Java API for storage, NoSQL, messaging, events, Kafka streams, SQL, caches, parameters, and secrets across AWS, Azure, and Google Cloud. Runs in-process with a Spring Boot starter, passwordless cloud IAM auth, and a conformance kit that verifies every provider.
Writing
OCTOBER 2026
Why the usual if-else feature toggle turns into debt, what a clean toggle design looks like in Java, and how Flipjack moves the decision out of your code.
Read article → AI · RAGSEPTEMBER 2026
Building a Qur’an and Hadith research tool where the LLM answers only from retrieved, verified sources — and two production failures that shaped the pipeline.
Read article → AI · Vector SearchAPRIL 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 →ALL POSTS
Java, 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.
Lightweight runtime feature toggles for Java and Spring Boot, without the if‑else in your code.
AI-enabled document management system and RAG (Retrieval-Augmented Generation) knowledge base.
Automated Adhan player for Raspberry Pi. Integrates with Bluetooth speakers including Amazon Echo.
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.