Software Engineer | Full-Stack Developer | Node.js, TypeScript, React, AWS
I build customer-facing web apps, backend APIs, and reliable cloud services.
Full-Stack Engineer with experience building customer-facing web applications, backend APIs, internal tools, and cloud-based services.
Hands-on across Node.js, TypeScript, React, REST APIs, AWS serverless, databases, testing, debugging, and production issue investigation.
Customer-facing workflowsProduction issue investigationCloud-based services
Event ledger
Event Bus
Event-driven flow
Watch idempotency, retries, outbox, and DLQ kick in.
Systems playground
Trace the flow, spot the safeguards.
Ctrl + K for command palette
Architecture Mode turns the whole site into a diagram-first view and highlights where each project lives.
Event-driven map
Service mesh in miniature
API gateways, compute, storage, and queues stitched with observability. Projects attach right where real incidents happen.
Core services Projects anchored to the flow Selected node
Focused node
REST APIs
Customer-facing endpoints, authentication, and product workflow contracts.
Reliability scorecard
How the systems stay calm under pressure
Patterns I ship by default. Hover or focus each row for why it exists.
SLO target
99.9%Experience
Frontend, backend, and production support across live products.
Expandable timeline
Fixfirst - Backend Engineer Germany (Remote) Production backend ownership Jan 2024 - Present
Fixfirst - Backend Engineer
Germany (Remote)
Production backend ownership
- Built and maintained backend services for customer-facing workflows using Node.js, TypeScript, AWS Lambda, SQS, SNS, Cognito, MySQL, and Sequelize.
- Developed REST API endpoints and backend logic to support product features, internal workflows, authentication, and asynchronous processing.
- Investigated and fixed production issues across Node.js and TypeScript APIs, AWS Lambda functions, SQS/SNS queues, CloudWatch logs, and MySQL records.
- Improved reliability through better error handling, retry logic, idempotency checks, structured logging, monitoring, and safer failure handling.
- Worked with frontend and product teams to clarify requirements, fix integration issues, and deliver maintainable backend changes.
What I shipped
- Backend services for customer-facing workflows
- REST API endpoints for product and internal workflows
- Authentication and asynchronous processing
How it ran in prod
- Production debugging across APIs, Lambda, queues, logs, and data records
- Retry logic, idempotency checks, monitoring, and structured logging
- Node.js, TypeScript, AWS Lambda, SQS, SNS, Cognito, MySQL, Sequelize
SMSAMI - FlyAwayHub product Pakistan Frontend to backend transition Jan 2021 - Aug 2023
SMSAMI - FlyAwayHub product
Pakistan
Frontend to backend transition
- Transitioned from frontend to backend engineering after applying internally and completing the company interview process.
- Worked on FlyAwayHub, a cloud-based aviation management platform supporting flight school bookings, resources, reporting, and operational workflows.
Backend Engineer
- Built and maintained backend APIs using Node.js, TypeScript, REST APIs, DynamoDB/Dynamoose, and cloud-based deployments.
- Developed backend features for booking workflows, operational dashboards, internal tools, and business processes.
- Debugged and resolved issues across backend APIs, data flows, and frontend API integrations for FlyAwayHub users.
Tech: Node.js, TypeScript, REST APIs, DynamoDB, Dynamoose, Jest, cloud-based deployments
Frontend Engineer
- Built responsive user interfaces for customer-facing screens, dashboards, forms, and internal workflow pages using React and TypeScript.
- Developed reusable frontend components and integrated screens with REST APIs for creating, updating, and managing application data.
- Worked on layout improvements, bug fixes, user experience improvements, and API integration issues across the platform.
Tech: React, TypeScript, JavaScript, REST API integration, HTML5, CSS3
What I shipped
- FlyAwayHub backend APIs and cloud-based deployments
- Booking workflows, operational dashboards, and internal tools
- Responsive React interfaces and reusable frontend components
How it ran in prod
- DynamoDB/Dynamoose data flows and API integrations
- Frontend-to-backend debugging across customer-facing workflows
- React, Node.js, TypeScript, REST APIs, DynamoDB, Jest
AYS Electronics - Junior Full-Stack Developer Pakistan Jun 2019 - Dec 2020
AYS Electronics - Junior Full-Stack Developer
Pakistan
- Worked on AYS Online, the company e-commerce website for electronics and home appliances, along with internal business tools.
- Built frontend screens and supported backend APIs for product, customer, order, and internal business workflows.
- Supported banking and payment-related integrations between the website, internal systems, and external providers.
- Collaborated with business users and technical teams to gather requirements, fix issues, test changes, and improve system functionality.
What I shipped
- AYS Online e-commerce workflows
- Frontend screens and backend APIs
- Internal business tools and payment-related integrations
How it ran in prod
- Product, customer, order, and internal workflows
- Relational databases and third-party integrations
- Python, backend APIs, frontend development, internal tools
Projects
Mini case studies with interactive demos.
Each project shows the problem, the engineering approach, and the operational outcome.
Sentinel Incident Platform
Alert ingestion, correlation, state management, retries, logging, and observability.
Architecture snapshot
Alert intake flows through retries, DLQ, and replay tooling.
Problem
Incident workflows break when alert events fail or arrive twice, making recovery slow and hard to audit.
Approach
- Designed event-driven intake with correlation IDs and idempotency at the edge.
- Modeled incident state changes with an outbox and DLQ for replayable recovery.
- Instrumented traces, metrics, and logs to tie failures to user impact.
Outcome
- Delivered resilient incident workflows with safe retries and replay tooling.
- Made failures traceable across services for faster triage.
How users interact with it
Operators ingest alerts, review retries, and replay failed events from a shared console.
What breaks first: downstream alert integrations stall, pushing retries into the DLQ and stretching recovery timelines.
Tradeoffs
- Chose: event-driven intake with idempotency + DLQ replay.
- Rejected: synchronous processing with manual incident recovery.
- Why: needed auditability and safe retries under real traffic spikes.
Incident console
Status: Idle
Latency
120 ms
Error rate
2.0%
No incidents yet. Trigger an event to start.
Correlation ID: cor-0e49a5 - Idempotency key: idem-f263c7
Key engineering decisions
- Idempotency keys gate alert retries to prevent double writes.
- Outbox events keep data changes and emissions consistent.
- DLQ + replay tooling isolates failures without losing events.
- Correlation IDs flow through logs, traces, and alerts.
Network Anomaly Detection
Detect and classify network traffic anomalies with KDDCUP99, feature engineering, and model evaluation.
Architecture snapshot
Feature scoring feeds the model and raises alerts at tuned thresholds.
Problem
Network traffic needs to be classified quickly so abnormal behavior can be surfaced before it spreads.
Approach
- Used KDDCUP99 data with feature engineering to prepare traffic signals for model evaluation.
- Compared K-Means clustering and Random Forest classification for anomaly detection tradeoffs.
- Exposed contamination and threshold controls to make precision and recall tradeoffs explicit.
Outcome
- Delivered anomaly classifications that can support monitoring and investigation workflows.
- Made model tradeoffs transparent for stakeholders.
How users interact with it
Analysts tune thresholds, compare models, and review highlighted anomalies in a time-series view.
What breaks first: traffic drift pushes false positives before thresholds are recalibrated.
Tradeoffs
- Chose: transparent model toggles with operator-tuned thresholds.
- Rejected: black-box auto-thresholding without operator context.
- Why: ops teams needed explainable tradeoffs between noise and misses.
Toggle between models and tune contamination vs threshold to see precision/recall tradeoffs.
Predicted Actual anomalies
Precision
100%
Recall
50%
K-Means groups similar traffic patterns and flags points far from expected clusters.
Key engineering decisions
- KDDCUP99 gives a repeatable benchmark for anomaly detection experiments.
- Standardized distance scoring keeps thresholds consistent across runs.
- UI surfaces precision and recall to guide operations teams.
Capability map
Technical skills pulled from the latest CV.
Languages
- TypeScript
- JavaScript
- Python
- SQL
Backend
- Node.js
- REST APIs
- API development
- Authentication
- Production debugging
Frontend
- React
- HTML5
- CSS3
- Responsive UI
- REST API integration
Cloud & DevOps
- AWS Lambda
- SQS
- SNS
- Cognito
- S3
- CloudWatch
- Docker
- CI/CD
- GitHub Actions
Databases & Testing
- MySQL
- PostgreSQL
- DynamoDB
- Sequelize
- Dynamoose
- Jest
- Unit testing
- Debugging
Production Practices
- Error handling
- Retry logic
- Idempotency checks
- Structured logging
- Monitoring
Certifications & Education
Applied AI, computer science, security, and data science.
Certified Ethical Hacker (CEH)
LearnPentest
Data Science & Machine Learning
Kamyab Jawan Programme
MEng Applied Artificial Intelligence
London South Bank University
Oct 2023 - Oct 2024
Relevant coursework: Machine Learning, Industrial Cyber-Physical Systems
BSc Computer Science
University of Agriculture, Peshawar
Aug 2016 - Oct 2020
Relevant coursework: Data Structures, Distributed Systems, Databases
Open to roles
Open to roles: Software Engineer / Full-Stack / Backend
London / hybrid / remote