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AI Engineer with 3+ years in Generative AI & LLMs
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with hands-on experience designing and deploying production AI systems across Generative AI, Large Language Models (LLMs), AI Agents, Intelligent Document Processing, OCR, Computer Vision, NLP, Voice AI, Retrieval-Augmented Generation (RAG), embeddings, vector databases, LoRA/QLoRA fine-tuning, workflow automation, ERPNext/Frappe customization, and business process automation. Experienced in building end-to-end AI solutions from model integration to deployment.
Sindh Board
Diploma · Fine Arts
N/A – Present
Zikpro
AI Engineer
March 1, 2024 – Present
India
AibyteC
Machine Learning Engineer
June 1, 2023 – February 29, 2024
India
Diffusion Planet
AI Engineer
January 1, 2022 – May 31, 2023
India
Zikpro AI Invoice OCR
June 24, 2026 – Present
Intelligent invoice extraction, validation, and ERPNext purchase invoice generation.
AI CRM Agent
June 24, 2026 – Present
Multi-channel lead qualification and sales automation.
RAG and Knowledge Systems
June 24, 2026 – Present
Enterprise document search and question answering.
Vision AI Solutions
June 24, 2026 – Present
OCR, image understanding, and document intelligence.
Certified AI Developer
PIAIC
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity (OCR, CRM, RAG, Generative AI) and experience across different companies (Zikpro, AibyteC, Diffusion Planet) suggest adaptability and a broad interest in AI applications. The focus on practical, deployable solutions indicates a fit for roles requiring tangible impact. However, the lack of non-professional projects or community involvement limits the assessment of broader cultural alignment.
Soft Skills & Operational Fit
The resume highlights practical application of AI in business contexts (e.g., invoice OCR, CRM agents), suggesting a results-oriented approach. The descriptions are concise, indicating clear communication of technical work. However, specific soft skills like teamwork, problem-solving methodologies, or leadership are not explicitly detailed.