Full-Stack + AI
Production React, Next.js, and Node.js systems integrated with LLM pipelines (LangChain/OpenAI).
About
Engineering with research-grade precision
Bridging full-stack engineering, cloud architecture, and financial modeling to build systems that scale and deliver measurable outcomes.
4+ Years
Experience
AI · Cloud · FinTech
Domains
MScFE + BSCS
Education
7+ Libraries
Open Source
Scroll
Full-Stack EngineeringAI & Agentic SystemsCloud ArchitectureFinancial EngineeringBlockchain & Web3Technical LeadershipData EngineeringSystem DesignQuantum ComputingDevOps & CI/CD
Full-Stack EngineeringAI & Agentic SystemsCloud ArchitectureFinancial EngineeringBlockchain & Web3Technical LeadershipData EngineeringSystem DesignQuantum ComputingDevOps & CI/CD
Who I am
A multi-domain engineer solving hard problems at scale
01
Optimized AWS Athena queries across 300M+ events for 12x faster performance
02
Built intelligent assistants with OpenAI, Vector Stores, and guardrails
03
Migrated 180K lines of code from JavaScript to TypeScript
04
Published 7+ open-source libraries on PyPI and NPM
05
Pursuing MSc Financial Engineering at WorldQuant University
06
Full scholarship for Quantum Computing — Google AI & IBM Quantum
“Computer Scientist with professional expertise in Web, Cloud, and AI-Driven Applications, skilled in building scalable and high-performance solutions using modern technologies and data-driven methods.
Strong foundation in Data Structures, Algorithms, and System Design, with a research interest in applying AI to finance, medicine, and defence. Adept at collaborative, open-source, and cross-functional environments, and dedicated to advancing technical and academic excellence through research and innovation.
300M+
Events Processed
12x
Query Speedup
75%
Bottleneck Reduction
80%
Setup Time Saved
Work experience
Companies that shaped my craft
Three roles across scale, product, and systems — each expanding my engineering frontier.
Nov 2023 – Present
Software Engineer Level II
Digital Dividend Global
- Optimized AWS Athena queries across 300M+ events — delivering 12× query speedup at enterprise scale
- Built AI support assistants with OpenAI, pinecone vector stores, and production-grade guardrails
- Migrated 180,000 lines of JavaScript to TypeScript across a critical platform codebase
- Reduced microservice bottlenecks by 75%, improving overall system throughput
AWSNext.jsTypeScriptOpenAILangChainNode.jsDynamoDB
Jul 2023 – Oct 2023
Frontend Engineer
Star Marketing
- Built high-conversion interfaces for B2B SaaS platforms shipped to multiple clients
- Improved page load performance by 40% through SSR, code-splitting, and lazy loading
- Developed a reusable component library adopted across 3 different client projects
ReactTypeScriptNext.jsTailwind CSSFramer Motion
Jan 2022 – Feb 2023
Software Engineer
Divine Virtuality
- Built Web3 DApps with Solidity smart contracts on Ethereum and Polygon networks
- Reduced project setup time by 80% via internal automation and reusable boilerplate systems
- Full-stack development: React frontend, Node.js backend, MongoDB, and on-chain integrations
SolidityWeb3.jsReactNode.jsMongoDBHardhatIPFS
Core strengths
What defines my engineering approach
A practical blend of engineering depth, systems thinking, and consistent delivery outcomes.
Cloud & Scale
Cost-optimized AWS architectures (Athena/Lambda) processing 300M+ events with 12x speedups.
Financial Engineering
Quantitative modeling and risk management fundamentals from MScFE background.
Systems Thinking
Designing for evolution with observability, failure tolerance, and CI/CD automation.
Technology ecosystem
Tools I work with daily
A curated stack spanning frontend, backend, AI/ML, cloud, and data — tested in production.
TypeScriptReactNext.jsNode.jsPython.NET CoreC#SolidityRustLangChainOpenAITensorFlowAWS LambdaS3DynamoDBAthenaKinesisDockerKubernetesTerraformPostgreSQLMongoDBRedisGraphQLTailwind CSSFigmaGitGitHub Actions
Expertise
Technical Skill Matrix
Key proficiencies mapped across the engineering spectrum.
MECore Systems
React/Next.js
95%
Node.js
90%
AWS Cloud
85%
Python
80%
TypeScript
98%
LLM Ops
75%
DevOps
82%
SQL/NoSQL
88%
Education
Academic foundation and continuous learning
Formal programs reinforcing systems thinking, quantitative rigor, and research methodology.
MSc Financial Engineering
2025 – OngoingWorldQuant University, Louisiana, USA — Financial Markets, ML in Finance, Deep Learning, Derivative Pricing, Stochastic Modeling, Portfolio & Risk Management.
BSc Computer Science — CGPA 3.76/4.0 (Cum Laude)
2019 – 2023Bahria University, Karachi — OOP, Data Structures, Algorithms, AI, Neural Networks, Parallel & Distributed Computing. 70% Merit Scholarship.
Quantum Computing Scholarship
2021 – 2022Full scholarship for QubitXQubit program sponsored by Google Quantum AI & IBM Quantum, taught by Stanford Professors.
MBA Scholarship (75%)
AwardedLeadership and Management from Valar Institute — Strategic thinking and organizational management.
Competencies
Technical Skill Matrix
A quantitative breakdown of my technical proficiencies.
TypeScript / JavaScript95%
React / Next.js95%
Python90%
Node.js90%
Agentic AI / LangChain85%
Cloud Architecture (AWS)85%
System Design85%
C++ / FinTech Modeling75%
Operating Principles
How projects stay fast and reliable
Execution patterns refined through years of production delivery across startups and enterprises.
01
Evidence-first decisions
Roadmaps guided by data, not assumptions, to maximize impact and reduce wasted effort.
02
Architecture for evolution
Systems designed for growth with observability, failure tolerance, and clean composability.
03
Human-centered delivery
Translating complex technical choices into clear business outcomes for every stakeholder.
04
Quality at velocity
Shipping fast without cutting corners through automated testing, CI/CD, and code review.
05
Measurable outcomes
Every engagement defines clear success criteria with quantifiable metrics.
06
Continuous improvement
Post-delivery reviews and knowledge sharing to compound team capability over time.
Every system I build is designed to outlive the sprint that created it.
Engineering philosophy — Farasat Ali
Engagement model
From research to real-world impact
A structured approach used across consulting, product, and platform engagements.
01
Step 01
Discover
Map constraints, opportunities, and measurable success criteria with stakeholders.
02
Step 02
Design
Shape architecture, delivery sequence, and user-value milestones with technical rigor.
03
Step 03
Deliver
Ship iterative releases with quality gates, CI/CD automation, and feedback loops.
04
Step 04
De-risk
Strengthen reliability, performance, security, and governance post-launch.
01
Discover
Map constraints, opportunities, and measurable success criteria with stakeholders.
02
Design
Shape architecture, delivery sequence, and user-value milestones with technical rigor.
03
Deliver
Ship iterative releases with quality gates, CI/CD automation, and feedback loops.
04
De-risk
Strengthen reliability, performance, security, and governance post-launch.
Platforms & Certifications
Certified and battle-tested
Platforms and tools validated by professional certifications and production deployments.
AWS
Certified Cloud Practitioner
Azure
Fundamentals (AZ-900)
TensorFlow
Developer Specialization
Docker
Production Deployments
Kubernetes
Orchestration
Terraform
Infrastructure as Code
OpenAI
AI/Agentic Systems
LangChain
RAG & Agents
Quantum
QubitXQubit Program
Blockchain
Solidity + Hardhat
Frequently asked
Common questions
Quick answers about working style, availability, and process.
I work on full-stack web applications, AI/ML integrations, cloud architecture, and data-intensive platforms. Most engagements are 4-16 weeks with clear milestones and deliverables.
I'm primarily focused on challenging engineering roles and consulting engagements. For full-time opportunities, I look for teams working on impactful problems with strong engineering culture.
Async-first via Slack or email with documented decisions. Weekly or bi-weekly sync calls for alignment. Pull requests include thorough context and reasoning.
Absolutely. I integrate into existing workflows, follow your coding standards and review processes, and consistently ramp up fast — typically productive within the first sprint.
Production-first. I build with guardrails, evaluation frameworks, and monitoring from day one. No demo-only solutions — everything is designed for reliability, scale, and maintainability.
Need a strategic engineering partner?
If you are scaling a product, modernizing systems, or integrating AI workflows, let's plan the next milestone together.