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Senior Backend Engineer · Distributed systems & multi-tenant architecture

Hassan Abrar

Systems that hold under pressure.

I design and run event-driven, multi-tenant backends in Java/Spring Boot and Node.js/TypeScript, from payroll for Saudi enterprises to real-time ad-fraud blocking.

Available for remote work · EU / US-East overlap

01 / Signal

Numbers from production

5+

years building and operating production systems

1K+

isolated tenant databases at 99.9% uptime

12

production microservices extracted from a monolith

10K+

concurrent users on a real-time chat system

  1. 01

    Model

    Domain boundaries, tenancy, failure modes.

  2. 02

    Build

    Event-driven services with clear contracts.

  3. 03

    Operate

    Dashboards, alerts, and calm releases.

FIG. 01 / How I work

02 / Architectures

Different problems. Deliberate architectures.

01 · Independent project · Sole architect and operator

ClickFortify

Real-time ad-fraud detection for Google Ads and Meta Ads

Problem · Advertisers lose budget to bots, VPN, proxy and data-center traffic. Invalid clicks have to be detected and excluded while campaigns run, not discovered in a report weeks later.

Constraints

  • Every advertiser is an isolated tenant
  • Exclusions must sync back into Google Ads and Meta ad accounts
  • Detection runs on live traffic, continuously

Key decisions

  • Event-driven microservices over NATS so collection, scoring and sync scale independently
  • Redis Bull job queues for retries and back-pressure on ad-platform API calls
  • Behavioural scoring with device fingerprinting and VPN, proxy and data-center filtering
Ad clickCollectorNATSScoringAds syncTenant DBs
FIG. 02 / System sketch · ClickFortify

Outcomes

  • Automated IP exclusion sync back to advertiser ad accounts
  • Live production database migration across 500+ tenant databases at near-zero downtime

Stack

Node.jsTypeScriptNATSRedis BullMongoDBNext.js
FIG. 02B / Live traffic firewall · simulation

02 · Senior Backend Engineer (contract) via Mission.dev

Masdr payroll platform

Enterprise fintech and payroll for large Saudi employers

Problem · Payroll, bank verification and disbursement run through one platform for large employers. A lost or duplicated message means someone is paid incorrectly.

Constraints

  • Multi-tenant, multi-database architecture
  • Strict API governance for partners and banks
  • Releases move through DEV, UAT and PROD on WebLogic

Key decisions

  • Asynchronous, event-driven JMS pipelines for payroll processing, bank verification and inter-service communication
  • API lifecycle on Apigee: rate limiting, authentication and authorization policy, request/response validation
  • Splunk dashboards and alerting aimed at payroll and verification incidents
ApigeePayroll svcBank verifyJMSTenant DBs
FIG. 03 / System sketch · Masdr payroll platform

Outcomes

  • Shorter time to diagnose production payroll and verification incidents
  • Tenant configuration and isolation extended as new enterprise tenants onboard

Stack

JavaSpring BootJMSApigeeSplunkJenkinsIBM UrbanCode DeployWebLogic

03 · Senior Software Engineer

Southville multi-tenant platform

From one monolith to 12 production microservices

Problem · A single monolith served every customer: one slow module or bad deploy touched all tenants, and onboarding a tenant was manual work.

Constraints

  • Keep the product running throughout the decomposition
  • Hard data isolation for every tenant
  • Logs spread across GCP and AWS

Key decisions

  • Decomposed into 12 services along domain boundaries
  • Database-per-tenant with dynamic schema resolution and automated provisioning
  • JMS event pipelines for salary disbursement and attendance
  • Central observability across Google Cloud Logging, AWS CloudWatch and Splunk
MonolithGatewayBookingPayroll+10 moreTenant resolver
FIG. 04 / System sketch · Southville multi-tenant platform

Outcomes

  • 1,000+ isolated tenant databases at 99.9% uptime
  • API response times improved by 40%+ through Redis caching and query work
  • Incident detection and resolution time reduced by 60%
  • Booking platform handling 10,000+ daily transactions

Stack

NestJSNode.jsSpring BootMongoDBPostgreSQLRedisJMSDockerKubernetes

04 · Builder

VoxRange

Voice AI and call analytics infrastructure

Problem · Voice products need telephony, transcription and natural speech in real time, without depending entirely on per-minute third-party APIs.

Constraints

  • Real-time audio paths
  • Self-hosted, finite GPU capacity

Key decisions

  • Real-time telephony pipeline with speech-to-text
  • Custom text-to-speech models trained on self-hosted GPUs
CallTelephonySTTCustom TTSGPU
FIG. 05 / System sketch · VoxRange

Outcomes

  • Production voice AI infrastructure covering telephony, speech-to-text and custom text-to-speech

Stack

TelephonySpeech-to-textText-to-speechSelf-hosted GPU

05 · Software Engineer

Lytics · PEMRA

Media monitoring and intelligence for the Pakistan Electronic Media Regulatory Authority

Problem · The regulator monitors live broadcasts across channels and needs to find, clip and review content quickly, in both Urdu and English.

Constraints

  • Continuous live video ingestion
  • Bilingual Urdu and English content

Key decisions

  • Live video ingestion and clipping
  • Automated Urdu and English transcription and translation
  • Metadata tagging feeding real-time oversight dashboards
Live TVIngest + clipTranscribe ur/enTaggingDashboards
FIG. 06 / System sketch · Lytics · PEMRA

Outcomes

  • One system for monitoring, search and regulatory oversight of broadcast content

Stack

Node.jsReactMongoDBPostgreSQL

Other work

03 / Experience

Where the work happened

  1. May 2025 – Present · Remote · Riyadh, Saudi Arabia

    Senior Backend Engineer · Mission.dev

    Client: Masdr

    Enterprise fintech and payroll platform serving large Saudi Arabian employers.

    • Own end-to-end feature delivery across Spring Boot microservices in a multi-tenant, multi-database payroll architecture.
    • Design asynchronous JMS pipelines for payroll processing, bank verification and inter-service communication.
    • Manage the API lifecycle on Apigee: rate limiting, auth policy and request/response validation.
    • Build Splunk dashboards and alerting that shorten diagnosis of payroll and verification incidents.
  2. Feb 2023 – Present · Lahore, Pakistan

    Senior Software Engineer · Southville Solutions

    • Led the decomposition of a monolith into 12 production microservices.
    • Architected multi-tenant infrastructure for 1,000+ isolated tenant databases at 99.9% uptime.
    • Built a NestJS/MongoDB booking platform handling 10,000+ daily transactions; improved API response times by 40%+.
    • Centralized observability across GCP Logging, CloudWatch and Splunk, cutting incident resolution time by 60%; mentored 5+ engineers.
  3. May 2021 – Jan 2023 · Lahore, Pakistan

    Associate Software Engineer · Stack Intel .IO

    Promoted from Software Engineer Intern (03/2021 – 05/2021).

    • Built real-time chat on Node.js, WebSockets and Redis Pub/Sub for 10,000+ concurrent users at 99.8% delivery.
    • Shipped sub-100ms push notifications with Socket.io and Redis Streams; integrated Stripe with zero security incidents.
    • Raised test coverage to 85% with Jest, Mocha and Supertest, reducing defects by 45%.
  4. Oct 2021 – Apr 2022 · Lahore, Pakistan

    Developer Head · MSP Community, University of LahoreLeadership

    • Led the developer track: technical sessions and hands-on support for student engineers.
  5. 2017 – 2021 · Lahore, Pakistan

    BS Computer Science · The University of LahoreEducation

    • Bachelor of Science in Computer Science.

04 / Technical index

Tools I ship with

Languages
JavaTypeScriptJavaScriptPythonSQL
Backend
Spring BootNode.jsNestJSExpress.jsFlaskDjango
Architecture
MicroservicesEvent-drivenMulti-tenantDistributed systemsRESTGraphQLWebSockets
Messaging & streaming
Apache KafkaNATSJMSRedis BullSocket.io
Databases
PostgreSQLMySQLOracleMongoDBRedisDynamoDB
Cloud & DevOps
AWS (EC2, S3, Lambda, RDS)GCPDockerKubernetesJenkinsGitHub ActionsIBM UrbanCode Deploy
Observability & security
SplunkCloudWatchGoogle Cloud LoggingELKOAuth2JWTApigee
Frontend & mobile
ReactReduxTailwind CSSReact NativeExpo

05 / Field notes

Engineer first. Architect by habit.

Hover to resolve · tap on touch screens

FIG. 00 / Field note · 31.5204° N · 74.3587° E · LAHORE

I'm a senior backend engineer with 5+ years building and operating production systems across enterprise fintech, adtech and high-volume SaaS. I work across both major backend ecosystems, Java/Spring Boot and Node.js/TypeScript, with depth in event-driven microservices, multi-tenant architecture and real-time data pipelines.

I led the decomposition of a monolith into 12 production microservices, architected multi-tenant infrastructure for 1,000+ isolated tenant databases at 99.9% uptime, and have mentored 5+ engineers. I work remotely with teams across Saudi Arabia, Europe and North America.

Languages I speak
English · Urdu
Currently exploring
Voice AI infrastructure: real-time telephony, speech-to-text and custom text-to-speech on self-hosted GPUs.

06 / Writing

Notes from production

All writing →

07 / FAQ

A few useful answers

What kind of work do you take on?

Senior backend roles and contracts: designing and building event-driven services, multi-tenant platforms, and breaking monoliths into services that can be deployed independently.

Where are you based, and which time zones do you cover?

Lahore, Pakistan (UTC+5). I work remotely and keep working-hour overlap with EU and US-East teams, and I've worked with teams in Saudi Arabia, Europe and North America.

Which stack do you prefer?

Both Java/Spring Boot and Node.js/TypeScript (NestJS) in production, with Kafka, NATS or JMS for messaging and PostgreSQL, MongoDB or Redis for data. I pick based on the team and the problem.

Can you work inside an existing team and codebase?

Yes, that's most of my work. I join through code review and architecture discussions, then take ownership of features end to end.

Do you help with observability and production incidents?

Yes. I have built Splunk, CloudWatch and Google Cloud Logging dashboards and alerting that cut incident resolution time by 60%.

How do we start?

Book a 30-minute call or email me what you are building and where it hurts. I reply within a day.

08 / Contact

Have a system that needs to scale? Let's make it hold.

Tell me what you're building and where it hurts. I usually reply within a day.