Resume

About

Engineering with range, but anchored in measurable delivery

I like work that is technically demanding, commercially meaningful, and hard to fake: scalable platforms, AI-native workflows, cloud modernization, data-heavy systems, and research-friendly product ideas.

4+ years

Professional span

8+

Open-source packages

20+

Technical articles

AI x FinTech

Current focus

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TypeScriptNext.jsReactNode.jsPythonAWSAgentic AIFinancial EngineeringBlockchainData SystemsOpen SourceMentorship
TypeScriptNext.jsReactNode.jsPythonAWSAgentic AIFinancial EngineeringBlockchainData SystemsOpen SourceMentorship

Positioning

A full-stack engineer who thinks like a systems architect and learns like a researcher

01

Open to research collaboration, speaking, mentorship, and university-facing opportunities.

02

Interested in FTE roles, consulting, contract work, and founder or operator collaborations.

03

Comfortable moving between product strategy, implementation detail, and platform-scale architecture.

“My foundation is in web engineering, but the work has expanded naturally into AI systems, event-driven cloud architecture, data processing, blockchain experiments, quantitative finance, and technical leadership.

I am especially interested in environments where product execution, research curiosity, and long-term architecture all matter at the same time.

300M+

Events per tenant optimized

12x

Large-query performance improvement

75%

Microservice bottleneck reduction

180K

Lines migrated to TypeScript

Work experience

Companies that shaped my craft

Three roles across scale, product, and systems — each expanding my engineering frontier.

2025 – Present

Software Engineer Level II

Digital Dividend Global

  • Modernized a legacy codebase into a clearer monorepo architecture with stronger workflows.
  • Led migrations around tooling, CI/CD, and infrastructure practices.
  • Improved responsiveness and global performance through sharper AWS delivery patterns.
TypeScriptReactNext.jsAWSTerraformYarn Workspaces
2023 – 2024

Software Engineer Level I

Digital Dividend Global

  • Built and improved CMS-backed platforms with payments, admin workflows, and reporting.
  • Integrated services such as Tamara, HyperPay, Apple Pay, Securiti.AI, and ZATCA.
  • Improved code quality through better indexing, query work, and deployment refinement.
JavaScriptNode.jsMongoDB.NETReactTerraform
2023 – 2023

Full Stack Engineer

Star Marketing Pvt. Ltd.

  • Saved infrastructure cost across ElastiCache, App Runner, and Amplify.
  • Supported migration from Payload CMS and MongoDB to Strapi and PostgreSQL.
Next.jsStrapiPayload CMSPostgreSQLAWS
2023 – 2023

Frontend Engineer

Star Marketing Pvt. Ltd.

  • Reduced initial load time by roughly 5x while supporting substantially more content.
  • Improved city-level SEO visibility for global-facing pages.
Next.jsJavaScriptSSRSEO
2023 – Present

Staff Engineer

TechNova Inc.

    GoKubernetesAWSgRPC
    2022 – 2023

    Software Engineer

    Divine Virtuality

    • Built reactive frontend experiences with TypeScript, Next.js, and component libraries.
    • Supported reliable deployments and uptime through AWS and Azure-oriented infrastructure work.
    TypeScriptReactNext.jsReact NativeAWSAzure

    Core Strengths

    Where I create the most value

    My strongest contribution usually comes from combining technical breadth with clear execution priorities and an ability to learn fast in unfamiliar domains.

    AI-native product engineering

    Designing assistants, agentic workflows, and knowledge systems that connect cleanly to real products, real data, and real user constraints.

    Cloud and data systems

    Improving throughput, reliability, and observability across Lambda-driven, Athena-heavy, and event-based architectures.

    Research-ready thinking

    Comfortable discussing experiments, methodology, modeling, and technical uncertainty with professors, labs, and academically minded teams.

    Mentorship and standards

    Helping teammates raise code quality, architectural judgment, and development velocity without losing clarity.

    Working Stack

    Tools I use in real delivery

    A practical stack shaped by shipped projects, not by trend-chasing.

    TypeScriptJavaScriptReactNext.jsNode.jsExpressPythonFastAPIC#.NET CoreAWS LambdaS3DynamoDBAthenaKinesisTerraformDockerMongoDBPostgreSQLRedisOpenAILangChainTensorFlowSolidity

    Expertise

    Technical Skill Matrix

    Key proficiencies mapped across the engineering spectrum.

    MECore Systems
    TypeScript
    97%
    React / Next.js
    95%
    Node.js
    92%
    Python
    88%
    AWS
    88%
    Agentic AI
    84%
    Data Systems
    86%
    Technical Leadership
    82%

    Education

    Academic direction with strong technical grounding

    My education path blends core computer science, scholarship-backed advanced learning, and an increasing pull toward finance, research, and graduate study.

    Foundations of Financial Engineering Certificate

    2025 - 2026

    WorldQuant University. Studying quantitative finance, econometrics, modeling, and AI-driven decision systems as part of a pathway toward deeper finance-oriented work.

    Bachelor of Science in Computer Science

    2019 - 2023

    Bahria University, Karachi. Graduated Cum Laude with a 3.76 / 4.0 CGPA and a 70% merit scholarship.

    Quantum Computing Scholarship Program

    2023 - 2024

    The Coding School / Qubit by Qubit program supported by Google Quantum AI and IBM Quantum, taught with curriculum prepared by leading universities.

    Leadership and Management Scholarship

    Scholarship awarded

    Received a 75% merit scholarship for an MBA in Leadership and Management at Valar Institute.

    Competencies

    Technical Skill Matrix

    A quantitative breakdown of my technical proficiencies.

    TypeScript / JavaScript97%
    React / Next.js95%
    Node.js / APIs92%
    Python / Automation88%
    AWS / Serverless88%
    AI Systems / LLM Workflows84%
    Data Engineering83%
    FinTech / Quant Foundations76%

    Operating Principles

    How I approach engineering work

    I care about clean systems, but I care even more about whether those systems serve real goals without creating unnecessary complexity.

    01

    Build for durability

    Architecture decisions should still make sense after the first sprint, the first new hire, and the first unexpected scale problem.

    02

    Prefer useful depth over surface-level breadth

    I would rather know a system well enough to improve it meaningfully than collect shallow familiarity for its own sake.

    03

    Translate technical complexity clearly

    Strong engineering matters more when founders, researchers, hiring managers, and non-engineers can understand the trade-offs.

    The best engineering work is ambitious enough to matter and disciplined enough to hold up when reality gets messy.

    Engineering philosophy — Farasat Ali

    Collaboration Model

    How I typically work with teams

    Whether the context is a company, professor, founder, or startup team, the delivery model stays grounded in clarity and momentum.

    01

    Clarify the real problem

    Define what success means, what constraints matter, and what type of collaboration actually fits.

    02

    Shape the technical direction

    Turn requirements into an execution path with reasonable scope, architecture, and trade-offs.

    03

    Ship with visible progress

    Keep communication clear, deliver incrementally, and reduce risk through steady implementation.

    04

    Leave behind leverage

    Document, hand over context, and make the result maintainable for the next phase of growth.

    Platforms

    Ecosystems I work across

    Comfortable inside modern product, cloud, AI, and infrastructure workflows.

    AWS

    Cloud and serverless delivery

    OpenAI

    LLM-powered assistants and workflows

    Terraform

    Infrastructure as code

    GitHub Actions

    CI/CD and automation

    Payload CMS

    Structured content systems

    Strapi

    Headless content architecture

    FAQ

    Questions people usually ask

    The short version of how I think about opportunities and fit.

    Yes. I am especially interested in research-adjacent software problems across AI, finance, data systems, and computational experimentation.

    No. I am open to FTE roles, consulting, contract work, technical advisory, startup collaboration, and strong project-based partnerships.

    Yes. I am open to mentorship, tech talks, workshops, speaking opportunities, and conversations that create value for engineering communities or academic circles.

    Teams that need someone who can move between architecture, implementation, debugging, AI integration, and platform thinking without losing delivery momentum.

    If the problem is meaningful, I'm interested in the conversation.

    That could mean research, hiring, advising, shipping a product, or helping a team make a complicated system easier to evolve.

    Contact Me
    Read the Blog

    Next Steps

    Continue exploring

    Why Research-Minded Engineers Build Better Products

    Research habits do not slow product delivery down. They improve how teams reason about uncertainty, evidence, and technical direction.

    Navigate

    What Financial Engineering Adds to Software Work

    Financial engineering changes how you think about latency, traceability, risk, correctness, and the relationship between software and consequential decisions.

    Navigate

    Mentoring Engineers Through Code Review Without Slowing Delivery

    Code review is one of the strongest mentoring surfaces in engineering, but only when it compounds judgment instead of turning into vague gatekeeping.

    Navigate

    Services

    Ways I can contribute directly.

    Navigate

    Projects

    Execution history and outcomes.

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    Profiles

    Public footprint across platforms.

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