Backend Engineer · Java · Streaming Systems

Mohammed
Wazahath
Hussain

Building scalable, secure content streaming services and high-performance backend infrastructure. Specialising in Java & Spring Boot, microservices, and event-driven architecture at production scale.

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About

Who I Am

I'm a Backend Software Engineer with 3.5+ years of experience designing and building scalable, high-performance systems. I specialise in Java & Spring Boot and building robust content streaming pipelines that serve millions of users reliably.

At Zee Entertainment (Zee5), I've architected and shipped backend services powering content rail systems, middleware data pipelines, and real-time event processing — all at production scale on GCP.

My focus is on systems that are low-latency, observable, and resilient: the kind of infrastructure that disappears into the background and just works, even under heavy load.

3.5+
Years of Experience
Kafka
Real-time Event Streaming
Zee5
Currently Working Here
GCP
Cloud Native

Skills

Tech Stack

⚡
Languages
JavaNode.jsSQL
🏗️
Frameworks
Spring BootSpring ReactiveREST APIs
🔄
Architecture
MicroservicesEvent-DrivenSystem DesignMiddleware
📨
Messaging & Search
KafkaSolrRedis
🗄️
Databases
PostgreSQLRedis
☁️
Cloud & DevOps
GCPDockerCI/CD

Experience

Where I've Worked

Zee Entertainment Enterprises Ltd.Nov 2023 – Present
Software Development Engineer 1
  • Developed and optimised backend services for content rail systems on the Zee5 platform, ensuring low-latency and high availability for millions of concurrent users.
  • Designed and built middleware pipeline services to process and transform raw CMS data for efficient indexing and retrieval in Solr.
  • Implemented event-driven workflows using Kafka to handle real-time content data processing at scale.
  • Improved search performance and relevance through Solr integration and fine-tuned query tuning.
  • Contributed to migration of core services to GCP, enhancing scalability and system reliability.
Zee Entertainment Enterprises Ltd.Jul 2022 – Oct 2023
Associate Software Development Engineer
  • Designed and developed a platform acting as a data pipeline bridge between Zee5 engineering and content production teams using Spring Boot.
  • Built scalable backend services and integrated Kafka for real-time event-driven processing across content workflows.
  • Improved system performance and reliability by identifying bottlenecks and systematically optimising backend workflows.
Zee Entertainment Enterprises Ltd.Jan 2022 – Jul 2022
Software Engineering Intern
  • Worked on backend feature enhancements and bug fixes using the Java Spring ecosystem.
  • Improved application performance and system efficiency through targeted issue resolution and code optimisation.

Projects

What I've Built

🏥
✓ Completed
Doctor Admin System — Hospital Management
A production-grade doctor administration platform with an AI-powered treatment recommendation engine. Doctors log in, access patient records (vitals, diagnosis, history, blood group, line of treatment), and receive AI-generated treatment suggestions which they can approve, reject, or annotate with clinical insights. Supports specialty and super-specialty doctors — surgeons, anaesthetists, and specialists — with runtime assignment and a structured handoff flow where a treating doctor's full case insights are visible to the assigned super-specialist.
JavaSpring BootPostgreSQLAI RecommendationsJWT AuthREST APIsDocker
📡
✓ Production
Content Streaming Pipeline — Zee5
Middleware pipeline services processing raw CMS data into search-optimised formats served to millions of users on the Zee5 platform. Built around Kafka for real-time event streaming and Solr for high-performance content search and retrieval.
JavaSpring BootKafkaSolrGCP
🔗
✓ Production
Content Production Bridge Platform
Internal platform bridging Zee5 engineering and content production teams — automating data flow, reducing manual handoffs, and enabling production teams to trigger and monitor content workflows programmatically.
Spring BootKafkaEvent-DrivenPostgreSQL
🤖
⚙ In Development
AI-Integrated Backend Service
A personal project to learn AI integration from the backend perspective — building a Spring Boot service that connects to LLM APIs, handles streaming responses, and exposes AI capabilities through clean REST endpoints. The goal is to understand how AI fits into real production backend architecture, not just as a wrapper but as a first-class component.
JavaSpring BootLLM APIsStreamingAI Integration

Currently

What I'm Exploring

Active Learning
AI Integration for Backend Engineers

I'm a backend engineer who believes AI isn't just a frontend feature — it belongs in the infrastructure layer too. I'm currently building hands-on experience integrating Large Language Models into Java/Spring Boot services: streaming responses, prompt design, context management, and how to expose AI capabilities through clean, production-grade APIs. The goal isn't to become an ML engineer — it's to understand how AI fits into the systems I already build.

Stack I'm exploring
Spring AI LangChain4j OpenAI API Ollama Vector DBs RAG Patterns
Building toward

AI-powered backend services that are observable, testable, and production-ready — not just prototypes.

Contact

Let's Build Something

Open to backend engineering roles, collaborations on streaming infrastructure, and interesting problems in Java & distributed systems.

wajjjaaa@gmail.com +91 88849 78791 LinkedIn GitHub