AI Solutions Architect

**About the Role** We are looking for an experienced AI Solutions Architect / Developer to join our team and lead the design, implementation, and continuous improvement of AI\-powered features within our education platform. This is a hands\-on technical role requiring someone who can work independently, review existing AI implementations, identify architectural improvements, and build scalable AI solutions from the ground up. The ideal candidate is comfortable working across the entire AI stack—from prompt engineering and RAG pipelines to model training, embeddings, vector databases, backend integration, and production deployment. **Key Responsibilities:** * Review and improve our existing AI implementation. * Identify architectural issues, performance bottlenecks, and security vulnerabilities. * Design efficient AI workflows that minimize token usage and API costs. * Build and maintain Retrieval\-Augmented Generation (RAG) pipelines. * Integrate Large Language Models (LLMs) such as Claude, GPT, Gemini, Llama, Qwen, or similar models into our in\-house platform. * Design prompt engineering strategies and evaluation frameworks. Implement human\-in\-the\-loop feedback systems for continuous AI improvement. * Build and maintain embedding pipelines and vector databases. * Develop AI services, APIs, and backend integrations. * Evaluate new AI technologies and recommend improvements. * Document AI architecture, workflows, implementation details, and best practices. Collaborate with software developers, QA engineers, and product teams to deliver production\-ready AI solutions. * Troubleshoot production AI issues and optimize response quality, latency, and cost. **Experience:** * 5\+ years of software development experience * with at least 2 years of hands\-on experience building production AI systems. **Required Skills:** **Artificial Intelligence** * Large Language Models (LLMs) * Prompt Engineering * Retrieval\-Augmented Generation (RAG) * Embeddings * Vector Databases * Semantic Search * AI Evaluation * AI Guardrails * AI Safety * AI Observability **Model Development** * Fine\-tuning * LoRA / QLoRA * Model Training * Dataset Preparation * Synthetic Data Generation * Model Evaluation * Reinforcement Learning from Human Feedback (RLHF) knowledge is a plus **AI Frameworks** * Experience with one or more: * LangChain * LlamaIndex * DSPy * CrewAI * AutoGen * Semantic Kernel **Vector Databases** Experience with one or more: * pgvector * Pinecone * Weaviate * Qdrant * Milvus * ChromaDB **Backend Development** Experience with: * Python (preferred) * FastAPI * REST APIs * PostgreSQL * SQL * Docker * Git **Cloud \& Infrastructure** Experience with: * AWS * Google Cloud * GPU deployments * Docker * Kubernetes (preferred) **What We're Looking** **For**: The successful candidate should be able to: * Work independently with minimal supervision. * Take ownership of AI architecture and implementation. * Review existing code and improve it. * Identify bugs before they become production issues. * Write clean, maintainable, and well\-documented code. * Think critically and propose better technical solutions. * Communicate technical concepts clearly with both technical and non\-technical stakeholders. * Work effectively both independently and within a collaborative development team. * Stay up to date with the rapidly evolving AI ecosystem. **Nice to Have:** * Experience building AI products, preferably for Education (EdTech). * Experience with multi\-agent AI systems. Knowledge of child psychology or educational assessment. * Experience deploying open\-source LLMs locally. * Experience with Hugging Face ecosystem. * Experience building AI evaluation pipelines. Knowledge of MCP (Model Context Protocol). Experience with speech recognition (Whisper), OCR, or computer vision. Interested Applicants can share their CV via; * email: * WhatsApp: \ **(NO CALLS)** Work Location: In person