Staff AI/ML Engineer (AI)

Location: United Kingdom, fully remote

Company

hirify.global builds cloud-native SaaS software that helps energy retailers reduce operating costs, improve billing accuracy and enhance customer experience through automation and AI-driven insight.

What you will do

• Lead the architecture, technical strategy and roadmap for hirify.global's shared AI/ML Platform.
• Design and build production-ready golden paths for Machine Learning, Generative AI and Agentic AI solutions.
• Establish standards for model lifecycle management, prompt versioning, deployment, serving, RAG, orchestration and secure tool access.
• Build MLOps and LLMOps capabilities covering evaluation, experimentation, observability, monitoring and cost management.
• Partner with Data Scientists, Platform Engineers, Data Engineers, Legal, Cyber Security, Risk and Product teams to operationalise safe, explainable and auditable AI services.
• Mentor ML Engineers and help establish the AI Engineering team, operating model and engineering standards.

Requirements

• Significant experience delivering production Machine Learning and AI solutions as an AI Engineer, ML Engineer, Software Engineer or Technical Lead.
• Experience operating at Staff Engineer, Principal Engineer or equivalent technical leadership level.
• Deep expertise in MLOps and production ML platforms, including deployment, serving, monitoring, evaluation and lifecycle management.
• Proven experience building and operating applications powered by Large Language Models, with hands-on experience in RAG, prompt engineering, evaluation frameworks and agentic AI workflows.
• Strong software engineering skills, ideally in Python, plus experience designing distributed systems and production services.
• Experience operating cloud-native AWS services using containers, Kubernetes, Infrastructure as Code and CI/CD.
• Strong understanding of platform engineering, developer experience and self-service platform design.
• Experience implementing AI governance, model safety, privacy controls and responsible AI practices.
• Ability to balance performance, cost, scalability and risk, and communicate technical concepts and trade-offs to technical and non-technical audiences.

Nice to have

• Experience with MCP or similar emerging standards.
• Experience building enterprise AI platforms for multiple product teams.
• Experience with lakehouse data platforms and data engineering ecosystems.
• Knowledge of regulated industries such as Energy, Utilities, Financial Services or Healthcare.
• Experience with Agentic AI architectures and tool-using AI systems.
• Familiarity with emerging AI observability, evaluation and governance tooling.

Culture & Benefits

• Remote-first working environment with offices in London and Nottingham.
• 25 days' holiday plus bank holidays, with the option to buy or sell five additional annual leave days per year.
• Vitality Health Insurance with private healthcare, virtual GP access, mental-health support and wellbeing perks.
• Pension with a 5% matched contribution.
• Regular team-wide and company-wide events, plus two volunteering days per year.