[Hiring] AI/ML Engineer, Internal Platforms @24-MAG

Role Description

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.

Qualifications

• 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

Core Technologies

• Python
• LLM APIs
• FastAPI
• LangChain
• LangGraph
• Related AI development tools

AI Systems Focus

• Retrieval-augmented generation
• Prompt engineering
• Tool calling
• Agent orchestration

Infrastructure Focus

• Cloud deployment
• Scalable backend services using AWS, GCP, Azure, or similar platforms

Product Focus

• Development and continuous improvement of an AI-powered recruiting agent