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Ayo Ajayi

Ayo Ajayi

Backend Engineer – AI-Powered Content Generation/Data Labeling Architect (Gluecharm)

Nigeria flagLagos, Nigeria
$70.00/hrIntermediateDon T DiscloseInternal Proprietary Tooling

Key Skills

Software

Don't disclose
Internal/Proprietary Tooling

Top Subject Matter

AI Content Generation
AI-Driven Labeling/Annotation API
Enterprise LLM Orchestration and Evaluation

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

Text GenerationText Generation
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection

Freelancer Overview

Backend Engineer – AI-Powered Content Generation/Data Labeling Architect (Gluecharm). Brings 8+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal and Proprietary Tooling. Education includes Higher National Diploma, N/A. AI-training focus includes data types such as Text and labeling workflows including Text Generation.

IntermediateEnglish

Labeling Experience

AI Manager API/LLM Orchestration Lead (GlueX Platform) – Data Labeling & Evaluation

TextText Generation
Owned orchestration, fine-tuning, and evaluation of LLMs powering the AI Manager API for GlueX platform's multi-provider text and conversational agents. Designed and deployed a semantic edit and embedding search flow that selects artifacts, generates labels, and propagates consistency patches based on model confidence scoring. Maintained authoritative JSON schemas and OpenSpec change requests to manage edit surface area, evaluating LLM and agent output for enterprise workflows. • Managed prompt engineering, semantic search, and edit propagation for AI-generated text. • Orchestrated and fine-tuned multiple LLM providers for label consistency and accuracy. • Used Arize Phoenix, Sentry, and Blinker for production tracing and monitoring. • Oversaw evaluation, red teaming, and continuous improvement of LLM outputs.

Owned orchestration, fine-tuning, and evaluation of LLMs powering the AI Manager API for GlueX platform's multi-provider text and conversational agents. Designed and deployed a semantic edit and embedding search flow that selects artifacts, generates labels, and propagates consistency patches based on model confidence scoring. Maintained authoritative JSON schemas and OpenSpec change requests to manage edit surface area, evaluating LLM and agent output for enterprise workflows. • Managed prompt engineering, semantic search, and edit propagation for AI-generated text. • Orchestrated and fine-tuned multiple LLM providers for label consistency and accuracy. • Used Arize Phoenix, Sentry, and Blinker for production tracing and monitoring. • Oversaw evaluation, red teaming, and continuous improvement of LLM outputs.

2025 - Present

Backend Engineer – AI-Powered Content Generation/Data Labeling Architect (Gluecharm)

TextText Generation
Designed and implemented JSON Patch-based LLM editing, where language models generate minimal, schema-validated text edits for AI-powered content. Built and maintained event-driven AI pipelines for content generation with orchestration of multiple large language models (LLMs) and semantic search techniques. Established versioned content nodes and applied automated surface area definition for machine-editable fields using JSON schema, overseeing LLM training and evaluation in production environments. • Led the integration of LangChain/LangGraph for multi-provider LLM orchestration. • Developed a schema-driven artifact system for expandability and control over editable fields. • Ensured AI outputs were minimal, validated, and traceable. • Enabled production observability and iterative fine-tuning with Arize Phoenix tracing.

Designed and implemented JSON Patch-based LLM editing, where language models generate minimal, schema-validated text edits for AI-powered content. Built and maintained event-driven AI pipelines for content generation with orchestration of multiple large language models (LLMs) and semantic search techniques. Established versioned content nodes and applied automated surface area definition for machine-editable fields using JSON schema, overseeing LLM training and evaluation in production environments. • Led the integration of LangChain/LangGraph for multi-provider LLM orchestration. • Developed a schema-driven artifact system for expandability and control over editable fields. • Ensured AI outputs were minimal, validated, and traceable. • Enabled production observability and iterative fine-tuning with Arize Phoenix tracing.

2025 - 2026

Full-Stack & DevOps Engineer (Visible Technologies) – AI/LLM Data Labeling & Evaluation

TextText Generation
Built API endpoints and backend orchestration for labeling, processing, and transforming text via language models and automated artifact selection methods. Designed backend data flows to enable unit-testable business logic decoupled from infrastructure, supporting integration and evaluation of LLM outputs for downstream consumers. Authored test suites validating accuracy and coverage of AI-generated labels for business-critical data fields. • Integrated FastAPI backend with domain-driven design for structured data labeling. • Implemented automated synchronous and asynchronous data processing pipelines. • Used pytest and Vitest for comprehensive validation of generated labels. • Documented schema and OpenAPI endpoints for consistent frontend consumption.

Built API endpoints and backend orchestration for labeling, processing, and transforming text via language models and automated artifact selection methods. Designed backend data flows to enable unit-testable business logic decoupled from infrastructure, supporting integration and evaluation of LLM outputs for downstream consumers. Authored test suites validating accuracy and coverage of AI-generated labels for business-critical data fields. • Integrated FastAPI backend with domain-driven design for structured data labeling. • Implemented automated synchronous and asynchronous data processing pipelines. • Used pytest and Vitest for comprehensive validation of generated labels. • Documented schema and OpenAPI endpoints for consistent frontend consumption.

2022 - 2024

Education

P

Petroleum Training Institute

Higher National Diploma, Computer Science

Higher National Diploma
2023 - 2024
F

Federal Polytechnic of Oil and Gas, Bonny

National Diploma, Computer Science

National Diploma
2018 - 2020

Work History

G

Gluecharm

Backend Engineer

N/A
2025 - 2026
O

Ovation Network

Backend & DevOps Engineer

N/A
2024 - 2025