Autonomous AI Career Intelligence Platform
Overview
I developed an autonomous AI-powered platform designed to automate the job discovery and evaluation process.
The system continuously analyzes job opportunities against a candidate profile and delivers ranked recommendations directly through Telegram.
Rather than relying on manual job searches, the platform transforms fragmented opportunities into actionable career intelligence.
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The Challenge
Job seekers often spend significant time reviewing opportunities that are poorly aligned with their qualifications, experience, or career goals.
The objective was to create a system capable of:
Monitoring opportunities continuously
Evaluating candidate-job fit automatically
Ranking opportunities by relevance
Delivering personalized recommendations in real time
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Solution
Intelligence Layer
Developed a scoring engine that evaluates:
Technical skills alignment
Professional experience relevance
Industry compatibility
Education requirements
Soft skills fit
Each opportunity receives a weighted score and detailed evaluation breakdown.
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Recommendation Layer
Beyond numerical scoring, the platform generates contextual insights explaining:
Why a role is a strong match
Which qualifications are missing
Potential competitive advantages
Areas for improvement
This transforms raw job data into actionable decision support.
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Infrastructure
The platform operates as an autonomous workflow deployed on Render.
Key capabilities include:
Automated opportunity monitoring
Data processing pipelines
AI-driven evaluation
Telegram notification delivery
Continuous 24/7 execution
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Operational Workflow
Candidate submits CV
System extracts and analyzes profile information
Opportunities are collected and processed
Matching engine evaluates compatibility
Ranked recommendations are delivered automatically
AI-generated insights explain each result
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Key Features
✅ Automated CV Analysis
✅ AI-Powered Matching Engine
✅ Explainable Scoring System
✅ Real-Time Job Monitoring
✅ Telegram-Based Delivery
✅ Continuous Cloud Deployment
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Outcome
This project demonstrates my ability to design and deploy production-ready AI workflows that bridge the gap between complex technical systems and real-world efficiency.
The result is an autonomous platform that reduces manual effort while improving the quality and relevance of career opportunities presented to the user.
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Packaging looks like graphic design. But every word takes physical space.
For Day 19, I built PACKSHIFT an interactive packaging experience where claims, languages, warnings and data become pressure on a finite surface.
It starts with the real 56 mm width of the carton.
Then you try to make everything fit.
Make the box smaller and the pressure becomes physical:
56 mm → pressure → CRACK → recovery → museum
The final package doesn’t just show the solution — it remembers the negotiation that produced it.
Underneath the public game is a deeper spatial compiler built with Blender + Three.js / React Three Fiber, where the same package can open, decompose, expose its dieline, redistribute information and refold.
Packaging is not a file. It is a compiled surface.
Full case study ↓
https://contra.com/p/3WBccUlM-packshift-packaging-is-a-compiled-surface
Live experience ↓
https://packshift-awd.pages.dev/
GitHub ↓
https://github.com/Faadil1/PACKSHIFT
Would love to know which moment lands most for you: Actual Size, the Hydraulic Press, or the Museum?
Professional software engineer help a business scale 73% up
Professional software engineer help a business scale 73% up
Built a real-time fraud detection engine at Meridian FinTech (Python, Scikit-learn, Kafka) that reduced fraudulent transactions by 43%, saving $1.2M in year one. Also led a zero-downtime migration of core banking APIs to AWS Lambda + API Gateway, cutting server costs by 55% and p99 latency from 820ms to 94ms. #FinTech #Python #AWS #MachineLearning
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Built NeuraChat — a multi-tenant AI conversational platform with context-aware memory, RAG pipelines, and MCP tool extensibility. Powers 50K+ simultaneous users using Python, LangChain, GPT-4, FastAPI, React, Redis, and AWS. #AI #LLM #RAG #Python #FastAPI
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Heavenkeys Ltd. — Vetted Partner Network & Delivery Portfolio
We design high-level technical strategies and assemble elite, vetted delivery teams to solve complex challenges at the intersection of technology, behavioral science, and regulated systems.
16 vetted delivery partners | 5,000+ team members | 400+ projects delivered | 30+ industries
Enterprise clients: AT&T, Microsoft, Google, BMW, Verizon, Shell, Honeywell, Toyota, BlaBlaCar, HubSpot, KFC, Burger King, SAP, Rolls-Royce, Atlassian, Societe Generale & more.
business@heavenkeys.ca | 819-510-0525 | BN: 752441949
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At Shopify, I led development of an AI-powered merchant analytics dashboard using LangChain + Claude API, enabling natural language queries over $2B+ in annual transaction data. Architected GraphQL federation across 14 microservices, cutting frontend load from 3.1s to 740ms. #Shopify #GraphQL #AI #TypeScript