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Asad Ullah

Asad Ullah

Consultant — AI Prompt Engineering, Luton AI

United Kingdom flagLuton, United Kingdom
$35.00/hrExpertAws SagemakerGoogle Cloud Vertex AI

Key Skills

Software

AWS SageMakerAWS SageMaker
Google Cloud Vertex AIGoogle Cloud Vertex AI

Top Subject Matter

LLM/SLM prompt engineering
AI-driven process automation
Content Summarization

Top Data Types

TextText
DocumentDocument
Computer Code ProgrammingComputer Code Programming

Top Task Types

Prompt + Response Writing (SFT)Prompt + Response Writing (SFT)
Entity (NER) ClassificationEntity (NER) Classification
Text GenerationText Generation
Fine-tuningFine-tuning
Question AnsweringQuestion Answering
ClassificationClassification
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection
Function CallingFunction Calling
Text SummarizationText Summarization
RLHFRLHF
Evaluation/RatingEvaluation/Rating
Red TeamingRed Teaming
TranscriptionTranscription

Freelancer Overview

I design and deliver AI-driven systems that move beyond prototypes into reliable, production-ready solutions. With a background in building scalable enterprise platforms, my work now focuses on applying Large and Small Language Models to real-world problems, enabling intelligent automation and decision support. My approach is grounded in architecture. I focus on building systems that are not only functional, but also reliable, controlled, and aligned with business needs. The emphasis is always on making AI systems usable in real-world environments, where consistency, trust, and performance matter.

ExpertEnglishUrduPashto

Labeling Experience

Consultant — AI Prompt Engineering, Luton AI

TextPrompt Response Writing SFT
As a Consultant at Luton AI, I established prompting standards and guardrails for LLM/SLM systems. My work involved prompt engineering and fine-tuning, focusing on output consistency, safety, and reliability. I also validated and iterated proof-of-concept solutions for AI-driven automation. • Led prompt engineering initiatives to optimize LLM/SLM performance. • Defined and implemented guardrails for consistent, safe outputs. • Designed prompt-response workflows for intelligent automation. • Evaluated and improved system outputs through iterative validation.

As a Consultant at Luton AI, I established prompting standards and guardrails for LLM/SLM systems. My work involved prompt engineering and fine-tuning, focusing on output consistency, safety, and reliability. I also validated and iterated proof-of-concept solutions for AI-driven automation. • Led prompt engineering initiatives to optimize LLM/SLM performance. • Defined and implemented guardrails for consistent, safe outputs. • Designed prompt-response workflows for intelligent automation. • Evaluated and improved system outputs through iterative validation.

2024 - Present

Principle Engineer — LLM Content Generation, Manager Voice

TextPrompt Response Writing SFT
As Principle Engineer at Manager Voice, I integrated LLM features for content creation, rewriting, and summarization using RAG pipelines and prompt engineering. My responsibilities included establishing guardrails and refining LLM-generated outputs. The work emphasized controlled, brand-specific language model results. • Developed LLM prompts for tailored content generation. • Implemented guardrails ensuring high-quality responses. • Integrated retrieval-augmented generation for context. • Optimized prompt workflows for product feature delivery.

As Principle Engineer at Manager Voice, I integrated LLM features for content creation, rewriting, and summarization using RAG pipelines and prompt engineering. My responsibilities included establishing guardrails and refining LLM-generated outputs. The work emphasized controlled, brand-specific language model results. • Developed LLM prompts for tailored content generation. • Implemented guardrails ensuring high-quality responses. • Integrated retrieval-augmented generation for context. • Optimized prompt workflows for product feature delivery.

2024 - 2025

Senior Development Engineer — NER Data Labeling, Ennov

TextEntity Ner Classification
At Ennov, I contributed to the integration of NLP features supporting data interpretation through entity recognition (NER) within pharmacovigilance and enterprise applications. My work included designing and applying entity labeling processes for NLP model improvement. I collaborated with cross-functional teams to deliver data for model training. • Developed entity recognition datasets for NLP modules. • Applied NER techniques within pharmacovigilance systems. • Enhanced enterprise tools with structured data labeling. • Supported AI/NLP model refinement through labeled data.

At Ennov, I contributed to the integration of NLP features supporting data interpretation through entity recognition (NER) within pharmacovigilance and enterprise applications. My work included designing and applying entity labeling processes for NLP model improvement. I collaborated with cross-functional teams to deliver data for model training. • Developed entity recognition datasets for NLP modules. • Applied NER techniques within pharmacovigilance systems. • Enhanced enterprise tools with structured data labeling. • Supported AI/NLP model refinement through labeled data.

2018 - 2025

Research Engineer — NLP Data Labeling, University of Bedfordshire

TextEntity Ner Classification
As a Research Engineer, I labeled textual data using AI and NLP techniques to improve context-aware retrieval models. My primary responsibility was entity and intent annotation for information retrieval tasks. This work contributed to more accurate, personalized search results for end users. • Labeled user queries for intent and entity extraction. • Designed context-aware entity annotation workflows. • Provided annotated data for personalized search model training. • Improved model accuracy through comprehensive data labeling.

As a Research Engineer, I labeled textual data using AI and NLP techniques to improve context-aware retrieval models. My primary responsibility was entity and intent annotation for information retrieval tasks. This work contributed to more accurate, personalized search results for end users. • Labeled user queries for intent and entity extraction. • Designed context-aware entity annotation workflows. • Provided annotated data for personalized search model training. • Improved model accuracy through comprehensive data labeling.

2014 - 2018

Education

U

UOB

Master of Science, Computer Security and Forensics

Master of Science
2011 - 2012
I

IBMS

Bachelor of Science, Information Technology

Bachelor of Science
2007 - 2011

Work History

M

Manager Voice

Principle Engineer

Remote
2024 - Present
L

Luton AI

Consultant

Luton
2024 - Present