AI Engineer with 5+ years in LLM-powered applications and scalable AI systems.
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Assessing your cultural and operational fit
AI Engineer with 5 years of experience designing and deploying scalable AI systems, specializing in LLM-powered applications, real-time AI, and retrieval-augmented generation (RAG). Experienced in building end-to-end AI solutions, from data pipelines and model integration to production deployment and system optimization. Currently contributing to the development of real-time conversational and multimodal AI platforms, with growing responsibility in system architecture, technical direction, and team leadership.
EPI Digital: International Multidisciplinary School
Software Engineering
September 1, 2021 – June 1, 2024
Higher Institute of Applied Science and Technology Sousse
Computer Science
September 1, 2017 – July 1, 2021
Sindibad Group
AI Tech Lead
July 1, 2025 – Present
India
Cercina.ai
Data Scientist & AI Program Manager
May 1, 2024 – May 1, 2025
India
Roundesk Technologies
Data Scientist
July 1, 2021 – May 1, 2024
India
Sinay.ai
Freelance Data Scientist
March 1, 2021 – July 1, 2021
India
GomyCode
Part-Time Machine Learning Instructor
November 1, 2018 – March 1, 2024
India
Cultural Fit Analysis
The candidate's experience spans various company types (startup, established group, freelance, educational), indicating adaptability to different work environments. Their involvement in teaching and organizing workshops suggests a collaborative and knowledge-sharing mindset. The breadth of projects, from real estate automation to VoIP network congestion prediction, shows a diverse interest and ability to apply AI in different domains, aligning well with dynamic and innovative team cultures.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and mentoring skills from their AI Tech Lead role. Their experience as an instructor also highlights communication and pedagogical abilities. The diverse project experience suggests adaptability and problem-solving skills. The focus on optimizing workflows and risk management indicates a practical, results-oriented approach.