Hello, I'm Malik.
Ten years of software engineering, 210+ projects at 5.0 on Fiverr, the last few years shipping LLM systems into real business software. Karachi, UTC+5.
Read about me →
Karachi, Pakistan · UTC+5
Open to new projects · replies within 24 hours
I build AI agents, web & mobile apps, and the API integrations that make them work in production.
10 years of software engineering: web apps, mobile apps and the back ends behind them. The last few shipping LLM systems into real business software. Not a chatbot that answers and stops.
The 24-hour read
Pick a problem. This is the shape of the read I'd send back within 24 hours.
RE: Invoices & documents
Pre-written · the real one follows a call
RE: Invoices & documents
- Approach
- Read the invoice, check it against your own systems, do the work: a bill in QuickBooks, a ticket in the helpdesk, a line in Slack.
- What breaks
- 429s, 5xx, timeouts — so retry with exponential backoff, duplicate and reconciliation checks, an approval threshold, and a replayable event log.
- Not AI
- I tell you when AI is the wrong tool. Sometimes a 40-line script beats an LLM: cheaper, faster, deterministic.
RE: CRM ↔ accounting sync
- Approach
- Two systems never designed to talk: webhooks, OAuth flows, rate-limited endpoints. Refunds, partial payments, and reconciliation handled automatically.
- What breaks
- Rate-limited endpoints and OAuth flows. Error handling, logging, and monitoring from day one, not after something breaks.
- Not AI
- Sometimes a 40-line script beats an LLM: cheaper, faster, deterministic. I say so even when the AI version would bill more hours.
- Proof
- Stripe ↔ QuickBooks sync for a logistics company. Has reconciled cleanly since launch without manual fixes.
RE: An assistant on your own data
- Approach
- Trained on your own data — Slack, Notion, Google Workspace, or your database — and answering with sources, so output is verifiable instead of confidently wrong.
- What breaks
- Confidently wrong answers. Sources on every answer make them verifiable; error handling, logging, and monitoring from day one, not after something breaks.
- Not AI
- I tell you when AI is the wrong tool. I say so even when the AI version would bill more hours.
- Tools
- Anthropic API · OpenAI API · open models · LangChain · LlamaIndex · RAG · Pinecone · Supabase pgvector · Chroma · evals
RE: An undocumented or legacy API
- Approach
- Third-party, undocumented, and legacy SOAP APIs: webhooks, OAuth flows, rate-limited endpoints. Half my career. Built to survive production, not just a demo.
- What breaks
- Rate-limited endpoints, OAuth flows, SOAP. Error handling, logging, and monitoring from day one, not after something breaks.
- Not AI
- Sometimes a 40-line script beats an LLM: cheaper, faster, deterministic. Either way, code you can hand to another developer: documented, structured, yours.
- Tools
- REST · GraphQL · webhooks · OAuth2 · SOAP · Python (FastAPI, Django) · Node.js (Express, NestJS) · PHP/Laravel · .NET/C#
RE: A web or mobile app
- Approach
- Screens and data first, then the build: React or Next.js on the web, React Native or Flutter for iOS and Android from one codebase, a Python or Node API shared by both. Ten years of shipping this.
- What breaks
- Auth edge cases, slow networks, offline states, app-store review. So milestone one is a working skeleton on a real device, with tests, CI and crash reporting from day one.
- Not AI
- Most of an app is not AI. I tell you which small part benefits from a model and build the rest as plain, fast, maintainable software you own.
- Tools
- React · Next.js · TypeScript · React Native · Flutter · Python (FastAPI) · Node.js · Postgres · Supabase · Stripe · CI/CD
- Timeline & cost
- Realistic estimates. Fixed scope, clear milestones, no surprise invoices.
AboutMalik Akhtar
- Based
- Karachi, Pakistan · UTC+5
- Overlap
- US mornings · EU afternoons
- Experience
- 10 years of software engineering
- Track record
- 210+ projects · 5.0 on Fiverr
- Replies
- Within 24 hours
- Language
- English
Hello, I'm Malik.
The engineer you hand the hard part to.
I've spent ten years building software for people who need it to work on Monday morning, not just in the demo. More than two hundred and ten projects with a 5.0 average rating on Fiverr, and enough production incidents to know what actually matters: honest scoping, boring reliability, and code you still own when I'm gone.
For the last few years that has meant putting LLMs to work inside real business systems — agents that read documents and take actions, assistants that answer with sources, integrations between tools that were never meant to talk. I like the unglamorous parts: retries, rate limits, logging, the monitoring that keeps a system running while you sleep.
I work from Karachi with clients in the US, UK, EU, Australia and the Middle East, overlapping US mornings and EU afternoons. You'll get written updates without asking, a realistic estimate, and a straight answer — including "you don't need AI for this" when that's the truth.
- 01
Honest scoping
A short scoping call before any estimate. I would rather tell you the project is simpler than you thought than take a bloated budget.
- 02
Boring reliability
Error handling, logging, and monitoring from day one, not after something breaks. Realistic estimates, fixed scope, clear milestones, no surprise invoices.
- 03
Code you still own
Documented, structured, yours. No lock-in, no black box, and support after delivery — I don't disappear at handover.
Work3 projects
Work
One you can open. Two I can only describe: client work stays private, so I show the shape of it instead.
01 AI operations agent live
Relay
Paper in. Actions out.
An AI operations agent that reads supplier invoices and customer emails, checks them against the company's own systems, and does the work: bills in QuickBooks, tickets in the helpdesk, a line in Slack.
- Role
- Design, backend and frontend. Solo project.
- Stack
- Python · FastAPI · LLM tool use · SSE · vanilla JS · pytest · live demo on Cloudflare Workers AI
- Guardrails
-
- Six tools with strict JSON schemas
- Duplicate and reconciliation checks
- Approval threshold
- Retry with exponential backoff for 429 / 5xx / timeouts
- Event log streamed over SSE — replayable, testable without a network
02 Client work · Logistics company
Stripe ↔ QuickBooks sync
Refunds, partial payments, and reconciliation handled automatically. Has reconciled cleanly since launch without manual fixes.
No public link — client work
03 Personal tooling
AI job-matching pipeline
Fetches listings, scores them against a profile, drafts proposals with an LLM, schedules follow-ups. FastAPI + SQLite + local dashboard, tested end to end.
No public link — personal tooling
What I build8 services
What I build
Systems that do the work. Not a chatbot that answers and stops. Pick one and the stage draws it.
-
AI agents & automation
Systems that do the work: process documents, qualify leads, research, draft, classify, and take real actions inside your tools. Not a chatbot that answers and stops.
-
AI inside your existing stack
LLMs wired into your CRM, database, admin panel, Google Workspace, Slack, Notion, HubSpot, Shopify, or a legacy system nobody wants to touch.
-
Complex API integration
Third-party, undocumented, and legacy SOAP APIs. Webhooks, OAuth flows, rate-limited endpoints, data syncs between systems never designed to talk. Half my career.
-
RAG chatbots & assistants
Trained on your own data, answering with sources so output is verifiable instead of confidently wrong.
-
Backend & workflow systems
The APIs, queues, schedulers, and pipelines underneath all of the above. Built to survive production, not just a demo.
-
Email infrastructure & deliverability
Multi-domain sending, SPF/DKIM/DMARC, custom tracking domains, warmup, API-level integration.
-
Web apps & custom software
Full products and internal tools: React and Next.js front ends on Python or Node back ends, admin panels, dashboards, and the APIs underneath. Ten years of shipping software that is documented, structured, and yours.
-
Mobile apps
React Native and Flutter apps that share the API, auth, and data of your web product: iOS and Android from one codebase, with the backend built to match.
How I workFrom first message to handover
How I work
I tell you when AI is the wrong tool. Sometimes a 40-line script beats an LLM: cheaper, faster, deterministic. I say so even when the AI version would bill more hours.
01 First reply · within 24 hours
An honest read
Send me the problem, even roughly. Within 24 hours you get an honest read on approach, timeline, and cost. If I am not the right person for it, I will tell you that too.
02 Scoping call · short, first
Simpler than you thought
A short call before any estimate. I would rather tell you the project is simpler than you thought than take a bloated budget. Sometimes a 40-line script beats an LLM.
03 Scope & milestones · fixed, written
No surprise invoices
Fixed scope, clear milestones, realistic estimates. I have been wrong enough times to know how long things take, so the plan is one you can hold me to.
04 Build · with written updates
You never have to ask
Regular written updates, so you always know the status. Error handling, logging, and monitoring from day one, not after something breaks.
05 Handover & after · support included
Code that stays yours
Documented, structured, yours: code you can hand to another developer, no lock-in, no black box. Support after delivery. I do not disappear at handover.
Stack6 layers · 46 tools
Stack
Everything orbits the product. Six layers, in the order a request travels through them, and the older ones I still add AI to.
-
01
Web & mobile apps
the apps people touch · 5
Products and internal tools: React and Next.js front ends, dashboards and admin panels, and React Native or Flutter apps that share the same API and data.
- React
- Next.js
- TypeScript
- React Native
- Flutter
-
02
Backend
the APIs and the logic · 6
FastAPI and Django in Python, Express and NestJS in Node: the APIs, queues, schedulers and pipelines underneath everything, built to survive production.
- Python
- FastAPI
- Django
- Node.js
- Express
- NestJS
-
03
AI / LLM
the reasoning, kept on a leash · 9
Agents with strict tool schemas and approval thresholds, RAG assistants that answer with sources, evals so the output is verifiable instead of confidently wrong.
- Anthropic API
- OpenAI API
- open models
- LangChain
- LlamaIndex
- RAG
- tool use
- MCP servers
- evals
-
04
Data & infra
where it lives and runs · 10
PostgreSQL first. Redis for queues and caching, vector stores for retrieval, Docker and AWS with CI/CD so deploys are boring and repeatable.
- PostgreSQL
- MySQL
- MongoDB
- Redis
- Pinecone
- pgvector
- Chroma
- Docker
- AWS
- CI/CD
-
05
Integration
the systems it has to talk to · 12
Half my career: third-party, undocumented and legacy APIs, webhooks, OAuth flows, rate limits, and syncs between systems that were never designed to talk.
- REST
- GraphQL
- webhooks
- OAuth2
- SOAP
- Stripe
- Twilio
- HubSpot
- Shopify
- n8n
- Make
- Zapier
-
06
Legacy
systems that already exist · 4
For adding AI and modern integrations to PHP/Laravel and .NET/C# systems that already exist and that nobody wants to rewrite.
- PHP
- Laravel
- .NET
- C#
What this stack has shipped9 kinds of work
210+projects delivered with a 5.0 average rating on Fiverr , over ten years, on this stack. Three of them are described in Work; these are the kinds of problems behind the rest.
- 01
AI agents & automation
“Read our documents and do the work in our tools.”
AI / LLMBackendData & infra
- 02
Assistants on your own data
“Answer questions from our docs, with sources.”
AI / LLMData & infra
- 03
Web apps & internal tools
“A product, an admin panel, a dashboard.”
Web & mobileBackendData & infra
- 04
Mobile apps
“iOS and Android, one codebase, same backend.”
Web & mobileBackend
- 05
CRM, accounting & payment syncs
“Make Stripe, HubSpot and QuickBooks agree.”
IntegrationBackendData & infra
- 06
Undocumented & legacy APIs
“Talk to a system nobody wants to touch.”
IntegrationLegacy
- 07
Backends & pipelines
“The queue, the scheduler, the API underneath.”
BackendData & infra
- 08
Email infrastructure
“Our mail lands in spam.”
BackendIntegration
- 09
Legacy upgrades
“Add AI to the PHP or .NET system we already run.”
LegacyAI / LLM
- 01
Boring on purpose
PostgreSQL before a new database, a queue before a framework, a 40-line script before an LLM. Deterministic wins when it can.
- 02
The right tool, not the newest
I tell you when AI is the wrong tool, even when the AI version would bill more hours. The stack serves the problem, not the other way round.
- 03
Yours to keep
Documented, structured, standard tools another developer can pick up. No lock-in, no black box, no framework only I understand.
ContactReplies within 24 hours
Within 24 hours: an honest read on approach, timeline, cost.
Send me the problem. Short scoping call first — I would rather tell you the project is simpler than you thought than take a bloated budget.