Muhammad Ahsan · Riyadh, Saudi Arabia
I design and deploy secure, autonomous multi-agent systems — LangGraph, CrewAI, and MCP, running in production.
Autonomy isn't prompted. It's engineered — part by part.
The orchestration pattern I run in production. This isn't a mockup — it's the real architecture pattern behind my production multi-agent systems.
The orchestration stack I build with — each grounded in real projects and certifications.
Built browser-integrated workflow sidekicks and the autonomous agent loops that automate client comms and vendor matching at Wanhar Impex.
Engineered autonomous agent teams that draft contracts and coordinate multi-step business workflows.
Designed multi-agent conversation networks and swarms for collaborative task decomposition.
Deployed multi-agent networks and orchestrators with Claude Code subagents, driving automated feature development wired into Jira and GitHub.
Orchestrated complex multi-agent systems and hand-off logic across specialized worker agents.
Built production multi-agent loops on AWS with Lambda, SQS, and Aurora Serverless for scale.
Integrated multi-server MCP environments so agents reach tools, data, and each other through a shared protocol.
Composed RAG chains and production interfaces over open-source vector datastores.
Instrumented LLM observability, cost tracking, and guardrails across production agent runs.
Fine-tuned and served open-source models; ran QLoRA on top of the HF ecosystem.
Runs high-velocity delivery with Claude Code, Cursor, and MCP — context managed via AGENTS.md and CLAUDE.md.
Cut LLM cost and latency with prompt/context compression, caching, and token budgeting — measured and tuned through LangFuse.
Run production LLM operations end to end — observability, cost tracking, guardrails, and evals — alongside classic MLOps.
Ship agents to production on AWS with Bedrock AgentCore, Lambda, SQS, and Aurora — automated via Terraform and GitHub Actions.
My agentic workflow methodology for shipping features fast with coordinated coding-agent teams.
Used Gastown to build and wire multi-agent workflows.
Wanhar Impex · Director & AI Engineering Lead
Shipment request enters the graph as typed state.
Goal decomposed into retrieve → draft → review → execute.
RAG over the vendor + freight vector store.
Bilingual RFQ and contract terms generated from context.
Security & privacy guardrails redact and approve.
Approved action dispatched through MCP tool servers.
Tokens, cost, and latency logged via LangFuse.
A real production workflow — condensed. Automates vendor sourcing, outreach, and contract drafting with a security gate on every hand-off.
A fully offline personal AI assistant running local LLMs at zero cloud cost.
A civilization sim where NPCs reason with local LLMs and remember via SQLite.
A high-performance scraper automating B2B lead generation and business auditing.
An ML pipeline predicting subscriber churn to power retention campaigns.
A replay study of a vehicle's keyless-entry signal using a HackRF One.
Multi-agent networks, swarms, and autonomous loops in production.
From inference to training — RAG, fine-tuning, and vector stores.
Serverless AI on AWS, Azure, and GCP — automated with IaC.
Classical ML, deep learning, and statistical modeling.
High-velocity delivery with agentic coding tools.
Including Google Advanced Data Analytics, Python 3 Specialization, EHE, and Agentic AI tracks.
TryHackMe leaderboard rank — backed by EC-Council Ethical Hacking Essentials and TryHackMe security certifications.
Across agentic AI, machine learning, live web and SaaS products, games, RF security, and IoT systems.
Leading AI, automation, and software delivery at Wanhar Impex since 2020.
Enterprise-grade agentic engineering: secure multi-agent systems, RAG over your private data, and custom LLM integrations — grounded, observable, and deployed serverless on AWS, Azure, or GCP.
40 documented certifications across agentic AI, data science, security, and engineering — the foundation under the work.
The foundations under the AI — security, data, and hardware.
Ethical hacking, forensic analysis, and secure-by-design pipelines.
Google-certified advanced analytics and statistical modeling.
RF communication, SDR, and physical sensor integration.
Available for AI Engineer, Generative AI Engineer, Machine Learning Engineer roles — on-site in Riyadh or remote worldwide.
