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Dan Lewis

Dan Lewis

Senior LLM Engineer (Agent Systems & Evaluation), Moniepoint

Kenya flagNairobi, Kenya
$12.00/hrExpertOther

Key Skills

Software

Other

Top Subject Matter

Conversational AI
Multi-domain Agent Systems
AI Dialogue Systems

Top Data Types

TextText
AudioAudio

Top Task Types

Function CallingFunction Calling
Emotion RecognitionEmotion Recognition
Text GenerationText Generation

Freelancer Overview

Senior LLM Engineer (Agent Systems & Evaluation), Moniepoint. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Bachelor of Science, University of Nairobi (2023). AI-training focus includes data types such as Text and labeling workflows including Function Calling, Emotion Recognition, and Text Generation.

ExpertEnglish

Labeling Experience

Senior LLM Engineer (Agent Systems & Evaluation), Moniepoint

TextFunction Calling
Responsible for designing high-quality multi-turn conversational datasets for simulating user interactions with AI assistants. Evaluated LLM outputs across reasoning, coherence, and correctness to identify performance gaps. Iteratively improved datasets based on feedback and model failures for better alignment and robustness. • Created datasets for AI assistant agent behaviors, including function-calling workflows. • Modeled structured tool interactions using JSON schemas for API alignment. • Generated edge-case and ambiguous scenarios to test system limits. • Improved clarity and realism in data, ensuring guideline adherence and logical sequencing.

Responsible for designing high-quality multi-turn conversational datasets for simulating user interactions with AI assistants. Evaluated LLM outputs across reasoning, coherence, and correctness to identify performance gaps. Iteratively improved datasets based on feedback and model failures for better alignment and robustness. • Created datasets for AI assistant agent behaviors, including function-calling workflows. • Modeled structured tool interactions using JSON schemas for API alignment. • Generated edge-case and ambiguous scenarios to test system limits. • Improved clarity and realism in data, ensuring guideline adherence and logical sequencing.

2022 - Present

Narrative Game Dialogue Design

OtherTextText Generation
Designed branching dialogue systems and interaction flows for narrative-driven environments. Structured multi-turn conversations to emphasize realism and engagement. Enhanced narrative immersion through decision-based dialogue annotations and structured progression. • Created and annotated story-based dialogues for AI narrative systems. • Focused on engagement and emotional depth in dialogue design. • Applied consistent structure to multi-turn conversational data. • Contributed to AI model improvement in RPG and storytelling domains.

Designed branching dialogue systems and interaction flows for narrative-driven environments. Structured multi-turn conversations to emphasize realism and engagement. Enhanced narrative immersion through decision-based dialogue annotations and structured progression. • Created and annotated story-based dialogues for AI narrative systems. • Focused on engagement and emotional depth in dialogue design. • Applied consistent structure to multi-turn conversational data. • Contributed to AI model improvement in RPG and storytelling domains.

Not specified

AI Dialogue Enhancement Project

OtherTextEmotion Recognition
Annotated conversational datasets focusing on emotional tone, realism, and engagement for AI dialogue systems. Enhanced multi-turn dialogue flows for more natural and coherent conversations. Evaluated dialogue for intent alignment, coherence, and context relevance. • Provided annotations on dialogue emotional tone and engagement. • Evaluated and rated dialogue quality for AI models. • Focused on multi-turn contexts and narrative realism. • Helped refine AI dialogue systems for improved user experience.

Annotated conversational datasets focusing on emotional tone, realism, and engagement for AI dialogue systems. Enhanced multi-turn dialogue flows for more natural and coherent conversations. Evaluated dialogue for intent alignment, coherence, and context relevance. • Provided annotations on dialogue emotional tone and engagement. • Evaluated and rated dialogue quality for AI models. • Focused on multi-turn contexts and narrative realism. • Helped refine AI dialogue systems for improved user experience.

Not specified

Education

U

University of Nairobi

Bachelor of Science, Informatics and Computer Science

Bachelor of Science
2019 - 2023

Work History

M

Moniepoint

Senior LLM Engineer (Agent Systems & Evaluation)

Nairobi
2022 - Present
M

MFS Africa

Senior Software Engineer (Backend & Workflow Systems)

Nairobi
2020 - 2022