
Asad Ali
Fullstack AI Engineer, AI Automation, AI Agents and SaaS Developer
Skills

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Portfolio
Work experience
AI Software Engineer
Fiverr • Freelance
Jan 2026 - Present • 9 mos
• AI & LLM Integration: Connect pre-trained models, LLM APIs (e.g., OpenAI, Anthropic, Google Gemini), and embedding services into existing web or mobile applications. • Feature Prototyping: Build functional Proofs of Concept (PoCs) and small-scale AI features (such as basic chatbots, RAG pipelines, or semantic search) under senior guidance. • Data Preparation & Pipelines: Write scripts to clean, preprocess, and format datasets for model fine-tuning, evaluation, or vector database ingestion. • Software Development & Coding: Write clean, modular, and maintainable code—primarily in Python or JavaScript/TypeScript—following team coding standards. • Testing & Debugging: Write unit tests, integration tests, and debug application or API failures related to model outputs and latency. • Collaboration: Work closely with senior engineers, product managers, and data scientists to translate business requirements into technical features. • Monitoring & Maintenance: Track basic model performance metrics, log API errors, and help patch or update deployed AI features.
AI Software Engineer
ArhamSoft
Dec 2023 - Jan 2026 • 2 yrs 1 mo
• AI & LLM Integration: Connect pre-trained models, LLM APIs (e.g., OpenAI, Anthropic, Google Gemini), and embedding services into existing web or mobile applications. • Feature Prototyping: Build functional Proofs of Concept (PoCs) and small-scale AI features (such as basic chatbots, RAG pipelines, or semantic search) under senior guidance. • Data Preparation & Pipelines: Write scripts to clean, preprocess, and format datasets for model fine-tuning, evaluation, or vector database ingestion. • Software Development & Coding: Write clean, modular, and maintainable code—primarily in Python or JavaScript/TypeScript—following team coding standards. • Testing & Debugging: Write unit tests, integration tests, and debug application or API failures related to model outputs and latency. • Collaboration: Work closely with senior engineers, product managers, and data scientists to translate business requirements into technical features. • Monitoring & Maintenance: Track basic model performance metrics, log API errors, and help patch or update deployed AI features.