AI/ML Engineer

JOB DESCRIPTION Own the end-to-end design, development and delivery of AI-powered features and services with some exposure to UI/UX design for in-house products, with a strong focus on business value. Collaborate with business stakeholders to gather, analyse and translate business requirements into AI/ML functional and technical solutions. Actively participate in Agile Scrum ceremonies, including sprint planning, backlog refinement, estimation, stand-ups, reviews and retrospectives. Specific Responsibilities: Design, develop and validate AI/ML and Generative AI proof-of-concepts (POCs) and prototypes to assess business value and technical feasibility. Build and integrate AI models, APIs and intelligent services into enterprise applications, with limited UI integration where required. Ensure deliverables meet established quality standards and agreed delivery timelines. Design and implement AI solutions in compliance with applicable regulatory, security, privacy and governance requirements. Identify and implement improvements in AI model performance, scalability, reliability, latency and cost efficiency. Evaluate and recommend emerging AI/ML technologies, LLMs, frameworks, tools and engineering approaches that can enhance product capabilities. Create and maintain technical documentation covering architecture, AI components, APIs, model configurations, deployment and operational procedures. Conduct comprehensive testing and evaluation of AI models, prompts, workflows and features for accuracy, relevance, reliability and production readiness. Implement telemetry using metrics, logs and traces to monitor AI solutions in production, troubleshoot issues and maintain service performance. Collaborate with data, application, infrastructure, cloud and security teams to successfully integrate and deploy AI solutions. Contribute to engineering best practices, reusable AI components, development standards and continuous improvement initiatives. Share technical knowledge, mentor team members and contribute to the overall technical capability of the AI engineering team. Take ownership of assigned work and remain accountable for its quality, maintainability, security and successful production delivery. Provide appropriate technical documentation and knowledge transfer to production support teams, including relevant third-party service providers. REQUIREMENTS Experience and Skills Required: Proven hands-on experience designing, developing and deploying AI/ML or Generative AI solutions within production software products. Strong experience with Python and AI/ML development frameworks and libraries. Experience developing solutions using LLMs, Generative AI, prompt engineering, embeddings, RAG and/or vector search. Experience building and integrating REST APIs and backend AI services into enterprise applications. Experience building and validating AI/ML POCs and prototypes to assess business value and technical feasibility. Strong requirements analysis skills, with the ability to translate business needs into technical AI solutions. Experience testing and evaluating AI models and features for accuracy, relevance, reliability and production readiness. Understanding of regulatory, security, privacy and governance considerations applicable to enterprise AI solutions. Experience with cloud-based AI/ML platforms and services, such as Azure AI/Azure OpenAI, AWS or equivalent technologies. Experience implementing telemetry, including metrics, logs and traces, and using observability tooling for production monitoring and troubleshooting. Ability to optimise AI solutions for performance, scalability, latency, reliability and cost. Familiarity with modern AI/ML tools, frameworks and development approaches, with the ability to assess their suitability for real-world use cases. Strong technical documentation skills covering solution architecture, AI components, APIs, deployment and operational processes. Experience working within Agile Scrum delivery models. Strong communication and collaboration skills, with experience working across data, infrastructure, application and security teams. Basic understanding of frontend/UI integration is desirable, but advanced UI/UX design or frontend development expertise is not required. Education Required: Bachelor's or master's degree in computer science, artificial intelligence, machine learning, software engineering, data science or a related discipline, or equivalent practical experience. Relevant certifications in AI/ML engineering, cloud AI platforms or software development are an advantage.