Software engineer · New York City

Software Engineer at Compass

I build reliable systems and thoughtful digital products from New York City.

Currently

Building
Small software projects and experiments
Learning
Systems, infrastructure, and better product engineering
Playing
Tennis
Exploring
NYC

Built in NYC · Between code and a tennis court

01 — About

About

A little context about who I am and what I like building.

The short version

Engineer, tinkerer, New Yorker.

I’m Safwan, a software engineer who enjoys building useful things and experimenting with technology. I care about reliable systems, clear product experiences, and the small details that make software feel considered. Away from a screen, I’m usually playing tennis or exploring another part of NYC.

A street scene in Lower Manhattan
Outside the screenWalking the city is usually where ideas get untangled.

What draws me in

  • Useful products with a clear reason to exist
  • Reliable systems and thoughtful infrastructure
  • Calm interfaces with careful interaction details

Tech I use

Next.jsTypeScriptReactTailwindNodeAWSKubernetesPostgreSQLSpring BootPython

Education

Stony Brook University — B.S. Computer Science (May 2024)

Certification

AWS Certified Solutions Architect – Associate (June 2025)

02 — Experience

Experience

Roles, impact, and the kind of problems I like working on.

Software Engineer

Compass — Platform / Notifications

Current
  • Work on platform systems that power notifications and customer communications across Compass.
  • Focus on email deliverability, reliability, and the operational health of communication workflows.
  • Partner across engineering teams to improve shared infrastructure and the experience of teams building on it.

Solutions Engineer

Appian — Cloud / DevOps / Production Support

Previous role
  • Resolved 500+ high-impact production incidents across AWS, Kubernetes, networking, and backend services.
  • Built internal automation and tooling to reduce manual operational overhead and improve cross-region handoffs.
  • Designed Grafana dashboards and OpenSearch log pipelines, improving debugging speed and system visibility.
  • Worked closely with infrastructure and product engineering teams to diagnose root causes and prevent regressions.
  • Regularly operated in high-pressure environments, prioritizing reliability, clarity, and ownership.

Software Development Engineer Intern

Amazon Web Services (AWS)

May 2023 — Aug 2023
  • Developed a CloudTrail visualization widget used by over 1M AWS customers to audit and explore account activity.
  • Built backend services using AWS Lambda, AppSync, DynamoDB, and S3.
  • Collaborated with senior engineers to design scalable APIs and production-ready infrastructure.
  • Focused on performance, security, and clear developer experience in customer-facing tooling.

03 — Selected work

Projects

A few thoughtful builds, from product ideas to focused technical explorations.

Featured project

Wayfeel

A location-based social app focused on expressive UI, calm interactions, and clean architecture.

Why it exists

An exploration of how a map-driven social product can feel expressive without becoming noisy.

  • Designed a map-driven interface with emoji-based markers and visual context
  • Built a serverless backend using GraphQL, Lambda, and Postgres
  • Focused heavily on UI polish, motion, and interaction details
Next.jsTypeScriptAWSAppSyncPostgreSQL

Tick

A personal finance and stock-tracking app built to explore full-stack architecture and data modeling.

Why it exists

A practical way to strengthen backend fundamentals through financial data and transaction workflows.

  • Designed backend APIs and schemas with clean separation of concerns
  • Explored financial data modeling and transaction workflows
  • Used the project to reinforce backend fundamentals and system design
Spring BootPostgreSQLREST APIsFinance

Fintech ML Sprint

A series of small machine learning experiments focused on market classification and signal exploration.

Why it exists

A focused way to build intuition around feature engineering and evaluation without chasing model complexity.

  • Built simple classifiers to explore SPY price movement signals
  • Focused on feature engineering and evaluation over model complexity
  • Used short, focused sprints to build intuition quickly
PythonMachine LearningPandasNumPy

04 — Lab notes

Lab

A looser space for experiments, useful scraps, and ideas in progress.

Workbench

Not everything needs to be a case study.

This is where smaller builds can stay small—and where unfinished can still mean interesting.

The workbench is getting set up

Small prototypes, Raspberry Pi experiments, self-hosted tools, utilities, and unfinished ideas will live here.

Coming soon

05 — Contact

Contact

Want to talk about software, cloud systems, or an interesting project?

Let's connect

I'm based in New York City. LinkedIn is the best place to send me a message, or you can browse what I'm building on GitHub.

Message me on LinkedInView my GitHub