Muneeb Ahmed

Prompt Engineer

Revelo

Jan 2026 - Apr 2026 (4 months)

• Designed and implemented prompts to evaluate LLM reasoning, accuracy, and response quality, recording findings in Git and sharing insights that guided refinements to improve model performance • Compared outputs from several AI models using scikit-learn metrics and SQL queries to evaluate performance, factual correctness, instruction-following, and coherence, producing a comparative report that informed model selection decisions • Conducted prompt-based testing across diverse scenarios with Pandas-managed test sets, uncovering model strengths, weaknesses, and edge-case behavior, which helped prioritize future testing focus • Documented evaluation results in a centralized REST-based repository and delivered detailed feedback, supporting ong

AI Contractor

Turing

Dec 2025 - Current (7 months)

• Develop AI training pipelines with TensorFlow and scikit-learn and engineer multilingual, multiturn prompts that improve model accuracy and response relevance • Create and review multilingual, multiturn prompts using prompt-engineering best practices, boosting LLM response quality and lowering error rates • Partner with global product and engineering teams, applying FastAPI and Django standards to meet project guidelines and consistently deliver on-time • Perform data annotation, response validation, and testing with Pandas and custom scripts, supporting model optimization and shortening iteration cycles

Mini repos

Revelo Talent Corp

May 2025 - Jan 2026 (9 months)

Business analyst

Turing

Jan 2025 - Feb 2026 (1 year 2 months)

LLM Agentic Function Calling Expert

Turing

Jan 2025 - Apr 2025 (4 months)

• Developed LLM-based agentic AI projects using FastAPI and MySQL to enable function calling, tool integration, and workflow automation, which streamlined data-retrieval processes and reduced manual effort • Designed and tested prompts for AI agents with Django and scikit-learn, achieving accurate function execution and reliable structured-data extraction across multi-step tasks • Evaluated model responses for reasoning, tool-usage accuracy, and context handling, pinpointing failure patterns and raising overall task-completion quality • Collaborated with product, engineering, and data-science teams to refine prompt templates and add validation checks, which reduced hallucination rates by 30% and raised conversational AI reliability, as refl

Senior Python Developer

Turing

Oct 2024 - Nov 2024 (2 months)

• Built and curated high-quality datasets for training and evaluating large language models using Pandas and custom scripts, enabling more reliable model evaluation • Designed Python pipelines with Docker and Pandas for data preprocessing, annotation, and validation at scale, streamlining the data workflow and shortening preparation time • Conducted prompt engineering, model testing, and performance analysis with scikit-learn, improving LLM accuracy by refining prompts and identifying weaknesses

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Senior Backend Engineer

TechSphere Solutions

Dec 2020 - Jun 2021 (7 months)

• Designed and implemented data pipelines and ETL workflows using Python, Django, and Apache Airflow to support predictive analytics, streamlining data preparation for model training. • Built customer churn models using Python, SQL, and scikit-learn, improving retention by 15%. • Developed demand forecasting models (ARIMA, Exponential Smoothing), reducing stockouts by 20%. • Created predictive maintenance models with TensorFlow, cutting equipment downtime by 25%. • Performed unit and integration testing of backend services with PyTest and Docker locally, catching 12 bugs before deployment and improving release stability • Configured FastAPI and Django services and set up backend environments with Docker and Git, which streamlined deployment

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Python Backend Developer

ByteWave Solutions

Jun 2019 - Nov 2020 (1 year 6 months)

• Developed and deployed RESTful APIs and microservices using Python (Flask, FastAPI), handling over 100K daily requests for SaaS applications. • Managed configuration files and CI/CD pipelines with GitHub Actions and Docker, debugged build and runtime issues before release, which shortened release cycles and improved deployment reliability • Built data automation pipelines using Pandas and NumPy to streamline reporting, reducing processing time by 50%. • Optimized PostgreSQL queries and caching layers, improving API response times by 35%. • Integrated third-party APIs with React.js frontend clients, ensuring consistent cross-platform functionality and reducing integration bugs. • Performed local testing of FastAPI services with pytest insi

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