We are sharing a specialised full-time remote opportunity for an experienced AI/ML Engineer with strong expertise in Python software engineering, large language models, AI agents, backend API development, and cloud infrastructure to build and enhance advanced AI-powered internal platforms. The selected professional will develop new capabilities for an AI recruiting agent, experiment with modern language models and agent frameworks, and deliver reliable, production-ready AI features. The role combines applied AI engineering with backend development, retrieval-augmented generation, agent orchestration, and continuous model evaluation to improve the accuracy, reliability, and practical effectiveness of intelligent recruiting workflows. Key Responsibilities - LLM Application & AI Agent Development - Design, develop, and enhance AI agent capabilities using modern large language models. - Build intelligent workflows that support recruiting-related tasks and automated decision-support processes. - Integrate LLM APIs and related AI services into internal applications. - Experiment with different model configurations and implementation approaches to improve agent performance. - Develop production-oriented AI features that deliver practical improvements to platform functionality. - Python Backend Engineering & API Development - Build and maintain backend services using Python and modern application development frameworks. - Design and implement APIs supporting AI-powered platform capabilities. - Develop backend integrations connecting models, application services, and relevant data sources. - Apply software engineering best practices to maintain reliability, scalability, and code quality. - Collaborate with engineering teams to deliver maintainable backend infrastructure and new product features. - Prompt Engineering, RAG & Agent Orchestration - Design and refine prompts, model workflows, and multi-step AI agent interactions. - Develop retrieval-augmented generation (RAG) capabilities for relevant knowledge retrieval and contextual reasoning. - Implement tool-calling and orchestration patterns for agent-based applications. - Evaluate and improve agent workflows using frameworks such as LangChain, LangGraph, or LlamaIndex. - Identify opportunities to improve model context handling, task execution, and workflow reliability. - Model Evaluation & Performance Optimisation - Evaluate the quality, accuracy, and reliability of AI-generated outputs. - Design experiments to compare model behaviour, prompting strategies, and agent implementations. - Identify weaknesses in AI system performance and implement targeted improvements. - Refine evaluation methods and quality metrics to support consistent performance assessment. - Apply experimental findings to improve the effectiveness and reliability of deployed AI features. - Cloud Deployment & Cross-Functional Product Delivery - Deploy, maintain, and improve AI-powered services in cloud environments. - Support scalable production operations using AWS, Google Cloud, Azure, or comparable infrastructure. - Collaborate with product and engineering teams to translate requirements into practical AI solutions. - Monitor emerging developments in LLMs, agent frameworks, and applied AI engineering tools. - Maintain high standards of technical documentation, implementation quality, and cross-functional communication. Ideal Profile - Strong professional experience in Python software engineering and backend application development. - Demonstrated experience building applications using large language models and AI APIs. - Practical knowledge of LLM integration, prompting, and AI application architecture. - Experience designing or implementing agent-based AI workflows. - Familiarity with LangChain, LangGraph, LlamaIndex, or comparable agent development frameworks. - Experience building backend APIs using FastAPI or similar Python frameworks. - Strong understanding of API design, service integration, and backend software engineering principles. - Practical experience working with at least one major cloud platform, such as AWS, Google Cloud, or Azure. - Understanding of scalable application architecture and production deployment practices. - Familiarity with retrieval-augmented generation (RAG) systems and relevant retrieval workflows. - Experience implementing tool calling, agent orchestration, or multi-step LLM applications is advantageous. - Strong analytical reasoning and software debugging capabilities. - Ability to experiment with different AI models and systematically evaluate results. - Experience assessing model performance, reliability, and output quality. - Strong understanding of prompt engineering and iterative AI application development. - Demonstrated ability to collaborate effectively with engineering and product teams. - Excellent written and verbal communication skills. - Strong independent problem-solving skills and an experimental approach to technical challenges. - Experience delivering production-ready AI applications or AI agents is strongly preferred. - Familiarity with model evaluation methodologies and practical AI quality assurance is beneficial. - Contributions to open-source AI projects or independently developed AI applications are advantageous. - Experience working in fast-paced, AI-focused technology environments is preferred. - Strong attention to detail and commitment to software reliability and maintainability. - Ability to manage technical priorities and deliver high-quality features in a remote environment. Engagement Details - Engagement Type: Full-time - Work Arrangement: Fully remote - Compensation: $220,000–$300,000/year - 1 available opening - Professional Focus: Applied AI engineering, LLM applications, AI agent development, and internal platform infrastructure. - Core Technologies: Python, LLM APIs, FastAPI, LangChain, LangGraph, and related AI development tools. - AI Systems Focus: Retrieval-augmented generation, prompt engineering, tool calling, and agent orchestration. - Infrastructure Focus: Cloud deployment and scalable backend services using AWS, GCP, Azure, or similar platforms. - Product Focus: Development and continuous improvement of an AI-powered recruiting agent. - Responsibilities will include building AI features, developing backend services, experimenting with model workflows, and evaluating system performance. - Assignments may involve API integration, RAG implementation, agent workflow development, cloud infrastructure, and production optimisation. - Deliverables will include production-ready AI capabilities, reliable backend services, evaluated model workflows, and technical documentation. - Previous experience shipping AI applications or intelligent agents to production is particularly relevant. - Strong Python engineering expertise, applied AI knowledge, independent problem-solving, and effective collaboration are important for successful performance. About the Platform This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information