Freelancer profile translated to English.
Back to original languageAbout Tijani
The promise:I deploy yourAI Agentsandautomationsto eliminate manual work.
Ex-AWSEngineer (Eurecom/EDHEC), I transform your operations throughAIand the Cloud. I don't just deliver scripts, but robust and profitable **AI Agents**.
🚀MY 3 PILLARS OF EXPERTISE:
AI Agents & Intelligent Assistants (RAG):This is the new frontier of productivity. I design tailor-made AI Agents connected to your data.
- Autonomous AI Agents for customer or internal support (instant responses).
- RAG (Retrieval Augmented Generation) Assistants querying your PDFs, Notion, or CRM.
- Stack: **n8n, Make, AI Agents**, LangChain, Amazon Bedrock, Vector DB.
Process & Workflow Automation:I replace your repetitive tasks withautomationsystems that run 24/7.
- Complex API connections (SaaS, ERP, Drive).
- Automatic data processing (Excel, CSV) via Python.
- Stack: **Automation**, Python, AWS Lambda, n8n/Make.
AWS Cloud & Data Architecture:For an AI Agent to be performant, it needs a solid infrastructure.
- Secure Serverless Architecture (optimized costs).
- Data cleaning and pipelines to feed your AIs.
- Stack: AWS, S3, DynamoDB, API Gateway.
💼CONCRETE ACHIEVEMENTS:
Challenge:Massive time loss searching for internal information.
Solution:Deployment of an AI Agent connected to procedures (SOPs).
Result:Instant responses, 3x efficiency.
Challenge:Impossible to manage a catalog of 900k products.
Solution:Serverless Automation Pipeline + Recommendation Engine.
Result:30% savings, processing in <5 seconds.
WHY ME?The technical rigor of an AWS Engineer to build reliable AI Agents, and the business vision (EDHEC) to guarantee ROI.
French
Native or bilingual
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- FreelanceCloud & GenAI EngineerTECHSeptember 2025 - September 2025Lille, FranceContext:Architecture and deployment of a recommendation engine "Secret Santa" (RAG) capable of mapping vague user intentions to a strict catalog of **900k+ products**.Impact & Architecture:*"Zero-Hallucination" RAG Architecture:Design of a decoupled pipeline. Use ofClaude Haiku(Bedrock) solely for semantic analysis, andAmazon Titan + Aurora pgvectorfor retrieval.Result: 100% of recommended products are real and in stock (no more LLM fabrications).*Performance & Scalability (Event-Driven):Integration ofAWS SQSandLambdato absorb load spikes (10,000+ users).Result: Latency maintained at< 5 secondseven under high competitive load.*FinOps & Governance (The strong point):Development of a real-time tracking module inDynamoDBto calculate the exact cost per request.Result: Optimization of prompts and models for an average cost of~$0.002 per transaction.*Express Delivery:Production-ready MVP delivered in < 1 week. Full documentation and deployment scripts provided for complete client autonomy.
- Amazon Web Services (AWS)Cloud Technical Business DeveloperTECHJune 2025 - September 2025 (3 months)Madrid, SpainContext:Automation of access to internal SOPs for Partner Program Specialists via AI.Impact:
- Internal AI assistant built with Amazon Q Business + Bedrock, connected to S3 documentation ➜ instant answers to operational questions.
- Python + Selenium + Lambda pipeline to extract dynamic content (menus, hidden sections) and synchronize SOPs with Amazon Q.
- Automatic alert system detecting SOP changes and updating S3.
- Integration of a lightweight UI (TamperMonkey + HTML) in Salesforce for smooth chatbot access.
- Fully serverless architecture (Lambda, API Gateway, S3) ➜ low cost, native scalability.
- Significant efficiency increase: elimination of manual navigation through long and complex SOPs.
- Amazon FranceVendor ManagerE-COMMERCESeptember 2024 - March 2025 (6 months)Paris, FranceContext:Management of the Low ASP category and improvement of the Office catalog quality.Impact:
- Python script (700 lines) integrating GenAI to identify and consolidate product duplicates ➜ reduction of losses (approx. €50 million annually) and improvement of catalog quality.
- Financial analysis to measure the impact of initiatives ➜ validation of profitability gains in the category.
- Implementation of a traffic redirection strategy to multipacks through negotiations with BIC, ACCO, Exacompta ➜ better EU customer experience.
- Management of the BTS project: traffic analysis, design & pitch of a GenAI tool (Bedrock) ➜ demonstrated potential CX improvement through market research.
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Education
- Master Computer ScienceEURECOMMaster en parallèle de mon cursus à l'EDHEC
- Master FinanceEDHEC Business School