Sekogo K.

Key Skills

Software

Other

Top Subject Matter

Strategic analysis

Generative AI

Natural Language Processing (NLP)

conversational AI

instruction tuning

Top Data Types

Computer Code Programming

Document

Text

Top Task Types

Text Summarization

Classification

Freelancer Overview

AI Engineer (Agentic search & n8n-based content handling/automation), HorizonTechServices. Brings 4+ 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, Bahria University, Islamabad Campus (2025). AI-training focus includes data types such as Document and Text and labeling workflows including Text Summarization, Computer Programming, and Coding.

Labeling Experience

AI Engineer - HorizonTech Services

DocumentClassification

As a full-time AI Engineer, he builds agentic AI systems using LangGraph with custom workflow nodes and persistent state handling. He also develops retrieval-driven context injection to improve the relevance of generated responses. The role requires strong skills in agent orchestration, RAG/semantic search, and automation pipeline development. • Built an agentic search system with LangGraph workflows and persistent state management. • Developed n8n automations for document processing, data routing, and access management to reduce manual effort. • Implemented intelligent content handling pipelines (summarization, classification, enrichment) for cross-team decision-making. • Created RAG-based semantic search for efficient vector retrieval and context-aware response generation.

2025 - Present

AI Engineer (Agentic search & n8n-based content handling/automation), HorizonTechServices

DocumentText Summarization

Built and automated document processing pipelines that analyze and transform uploaded or generated files for faster downstream decision-making across teams. Implemented retrieval-driven context injection and persistent state handling in an agentic search workflow to support content-aware processing. These activities function as AI training/data-prep style labeling via summarization and enrichment rather than manual annotation. • Automated extraction and classification/enrichment of uploaded or generated documents/files • Summarized content to produce structured insights for team decision-making • Routed processed data through internal workflow stages using automation • Reduced manual effort by replacing repetitive content handling with AI-assisted flows

2025 - Present

AI Business Development Executive, OctaloopsTechnologies

Text

Analyzed client requirements and researched AI technologies to propose tailored AI solutions for a freelancing platform. This work supports the definition and evaluation criteria for AI systems but does not involve direct annotation. It contributed to selecting approaches that can guide later data-labeling and AI training pipelines. • Gathered client needs and translated them into AI solution proposals • Researched AI technologies and trends for high-impact proposals • Defined problem framing that would inform future model training inputs • Produced tailored recommendations for stakeholders on AI feasibility

2025 - 2025

Software Engineer, DaxnoSolutions

OtherText

Developed backend features using Python and tested with real-world datasets, contributing to AI-enabled application components. While not explicitly framed as labeling, the work indicates dataset handling and preparation for model or analytics workflows. Responsibilities included clean modular code and integration of services that likely support AI data processing. • Implemented and integrated backend features using Python • Tested features with real-world datasets • Optimized system architecture to align with product requirements • Collaborated in sprints, code review, and Git workflows to support data-driven features

2024 - 2024

I do not have formal experience in data labeling or annotation roles

I do not have formal experience in data labeling or annotation roles. However, I have hands-on experience building AI systems, including RAG applications, sentiment analysis models, and fine-tuning workflows. Through these projects, I have worked with data preprocessing, cleaning, validation, and preparing datasets for machine learning models. I am comfortable learning annotation tools and can quickly adapt to data labeling workflows.

Not specified

Education

Work History