BAG Technologies is an AI-powered HR tech platform that transforms talent acquisition and development in Africa. We help organizations streamline high-volume recruitment through automated candidate ranking while building systematic talent pipelines using scenario-based assessments and skill development pathways.

We are seeking an experienced AI Application Developer to design, build, and deploy intelligent applications that integrate cutting-edge AI capabilities. This role focuses on leveraging existing AI models and APIs to create innovative user experiences, AI agents, and automated solutions that solve real business problems.

• Bachelor's degree in Computer Science, Software Engineering, or related field

• 3-5 years of experience in software development with at least 1-2 years focused on AI/ML application development

• Strong programming skills in Python, JavaScript/TypeScript, or similar languages

• Experience integrating and working with AI APIs and services (e.g., OpenAI, Hugging Face, etc.)

• Proficiency in web development frameworks (React, Angular, Vue, etc.) and/or mobile development

• Knowledge of RESTful API design and implementation

• Understanding of prompt engineering concepts and techniques

• Experience with cloud platforms (AWS, Azure, GCP) and serverless architectures

• Familiarity with version control systems (Git) and CI/CD pipelines

• Strong problem-solving skills and attention to detail

• Excellent communication skills and ability to explain technical concepts to non-technical stakeholders

• Programming Languages: Python, JavaScript/TypeScript, Node.js

• AI Integration: Experience with OpenAI API, Hugging Face, Anthropic Claude, or similar AI services

• Backend Development: Expert-level proficiency in Node.js frameworks (Express, NestJS, Koa) or Python backend frameworks (Flask, FastAPI, Django) for AI application development, with preference for Node.js expertise

• Software Architecture: Proficiency in designing and implementing standardized software architecture principles across a broad range of applications, teams, and products

• Database Management: Experience with SQL and NoSQL databases, vector databases for AI applications

• Cloud Platforms: Familiarity with AWS, Azure, or Google Cloud for deploying AI applications and agents

• API Development: RESTful API design and implementation

• Version Control: Git and GitHub/GitLab workflows

Good to have (optional)

• Testing: Unit testing, integration testing, and test automation

• DevOps: CI/CD pipelines, Docker containerization

AI Integration & Development

• Fine-tune large language models (LLMs) including LLaMA, Mistral, and Falcon on proprietary datasets to enhance performance in automation and customer support workflows

• Design and deploy AI agents capable of task execution and decision-making, leveraging retrieval-augmented generation (RAG) to improve accuracy and relevance

• Build and optimize RAG pipelines with advanced chunking strategies, embedding models, and retrieval mechanisms

• Implement custom training and fine-tuning workflows for domain-specific AI applications

• Design sophisticated AI agents and autonomous systems using existing AI models and APIs

• Build intelligent automation workflows and complex agentic AI solutions

• Implement advanced prompt engineering strategies and AI model orchestration

• Create robust backend systems that power AI-driven applications and services

• Develop scalable AI agent architectures with proper memory, tools, and decision-making capabilities

• Design and implement model evaluation frameworks to measure fine-tuning effectiveness and agent performance

Product Development

• Collaborate with product managers and designers to define AI feature requirements

• Prototype and iterate on AI-powered features based on user feedback

• Conduct testing and quality assurance for AI applications

• Monitor and analyze AI application performance and user engagement

• Stay current with emerging AI technologies and integration opportunities

Education

• Bachelor's degree in Computer Science, Engineering, or related technical field, or equivalent practical experience

Skills

• Backend Engineering: 2-4 years of experience working as a backend engineer

• LLM Experience: At least 2 years of hands-on experience working with Large Language Models

• Expert-Level AI Knowledge: Expertise in Agentic AI, LLMs, and AI model fine-tuning is essential. You should be considered an expert in leveraging existing AI models to build sophisticated agents and tooling, with proven application to existing products

• AI & ML Fundamentals: Solid understanding of basic AI and Machine Learning concepts that support effective model fine-tuning and optimization

• Model Fine-Tuning: Hands-on experience fine-tuning open-source LLMs (LLaMA, Mistral, Falcon, etc.) on proprietary datasets for specific use cases

• RAG Systems: Advanced experience designing and implementing retrieval-augmented generation (RAG) systems with vector databases and embedding optimization

• Agent Architecture: Deep understanding of AI agent design patterns, including tools, memory systems, and orchestration frameworks

• Agentic AI Solutions: Extensive experience building complex Agentic AI solutions and multi-step agentic workflows

• AI Agent Frameworks: Advanced experience with AI agent orchestration frameworks and tooling for building sophisticated AI agents

• Multi-Tenant Architecture: Ability to design multi-tenant backend systems that simplify GenAI for application teams

• Data Processing: Experience working with large datasets for training and operating AI agents, including data preprocessing and model evaluation

• Deep understanding of AI model capabilities, limitations, and optimization strategies

• Advanced prompt engineering and AI model fine-tuning experience

• Knowledge of AI safety, reliability, and responsible AI practices in production systems

• Expertise with vector databases, embeddings, and semantic search technologies

• Experience with model deployment, monitoring, and A/B testing for AI systems

Portfolio Requirement: Candidates must present a real-world AI project they have built, demonstrating hands-on experience with AI agents, model fine-tuning, or RAG systems. This serves as a practical assessment of technical capabilities and helps validate claimed experience.

• Experience building conversational AI agents with complex tool integrations

• Knowledge of natural language processing concepts and agent memory systems

• Advanced experience with AI orchestration frameworks (LangChain, LlamaIndex, AutoGen, etc.)

• Experience with real-time applications and WebSocket connections

• Understanding of AI ethics and bias mitigation strategies

• Experience designing scalable multi-tenant SaaS platforms

• Previous experience in startups or fast-paced technology environments

• Intelligent customer service chatbots and virtual assistants

• AI-powered content generation and editing tools

• Automated document processing and analysis systems

• Smart recommendation engines and personalization features

• Voice-enabled applications and multimodal AI experiences

• Lead AI product development initiatives

• Mentor junior developers in AI integration best practices

• Contribute to AI strategy and technology roadmap decisions

• Opportunity to work with cutting-edge AI technologies as they emerge

• Conference speaking and thought leadership opportunities in AI development

• Company issued latest MacBook Pro (on completion of probation period)

• Competitive salary commensurate with experience

• Equity participation in company growth

• Flexible work arrangements and remote-friendly culture

• Access to latest AI tools and technologies for professional use