AI & Agent Development Engineer

Tongston Entrepreneurship Group, a multi-award-winning brand providing entrepreneurial education, media, enterprise, and finance services, is recruiting an AI & Agent Development Engineer. This 100% remote 12-month independent contractor role will translate Tongston’s AI strategy, KB logic, and model-routing decisions into production-ready AI workflows within T-World, Tongston's AI-powered digital entrepreneurial ecosystem.

Key Details

• Job Title: AI & Agent Development Engineer

• Location: Remote

• Employment Type: Contract (12-month full-time paid independent contractor engagement)

• Compensation: ₦175,000 monthly fee + Remote Productivity Support Package + ₦200,000 L&D budget + Company laptop

Key Responsibilities

• AI Workflows & Agent Engineering: Build, implement, and operationalize AI agents, retrieval flows, and LLM-powered features using frameworks like Flowise, Dify, LangChain, LangGraph, or LlamaIndex.

• Multi-Model Orchestration: Support T-World’s multi-layer AI architecture by combining open-source LLMs, embeddings, internal knowledge base (KB) logic, and closed-model APIs while managing model routing, fallback logic, and cost optimization.

• Infrastructure & API Integration: Develop backend API services (Node.js/Express, MongoDB) and integrate cloud/compute workflows (AWS S3, Lambda, Step Functions, Bedrock) to power web and mobile AI interactions.

• Codebase Management & CI/CD: Commit clean, maintainable AI code to the T-World GitHub repository, using pull requests, version control, and automated testing via GitHub Actions.

• System Resilience & Testing: Implement error handling, loading states, logging, and fallback behaviors for weak inputs, partial failures, or AI timeouts to guarantee production readiness.

• Governance & Security Compliance: Enforce backend permissions, Firebase authentication, visibility rules, data-source controls, and moderation standards across all AI-generated outputs.

Requirements & Qualifications

• Education: Degree, HND/ND, current study, or equivalent practical experience in Computer Science, Software Engineering, AI/ML, Data/Analytics, Mathematics, or related fields.

• Experience Level: Ideal for early-career engineers with practical experience in backend systems, LLMs, AI agents, API integrations, and retrieval workflows (via projects, internships, hackathons, or professional roles).

• Technical Stack Proficiency: Hands-on knowledge of Node.js, Express, MongoDB, REST APIs, Git/GitHub, and Firebase Authentication.

• AI & Cloud Technical Exposure: Practical understanding of LLM orchestration, open-source models (Hugging Face), retrieval systems (vector DBs/embeddings), and AWS cloud tools (S3, Lambda, Bedrock).

Core Competencies

• Proven ability to design and build agentic workflows, prompt orchestration, function calling, and fallback mechanics.

• Strong problem-solving skills for debugging end-to-end flows (UI → API → AI Orchestration → Retrieval → Database → Output).

• High attention to detail regarding cost consciousness, system latency, security controls, and clean code documentation.

• Excellent self-management and collaboration skills in a remote, sprint-based Agile environment.