AI Engineer

• Serve as the subject matter expert for Microsoft Purview, Copilot, and Agent 365
• Lead the design and implementation of Microsoft Purview deployments aligned with customer requirements and best practices
• Deliver secure and compliant AI engagements using Agent 365, Azure OpenAI, Azure Machine Learning, and Microsoft Cognitive Services
• Monitor evolving data privacy and AI compliance regulations and ensure client controls remain aligned
• Provide technical leadership and mentorship to engineering teams
• Collaborate with internal stakeholders to grow organisational knowledge
• Act as a trusted advisor to clients and develop data security and AI strategies
• Support sales with client scoping, RFP responses, and proposal authoring
• Own CyberOne’s Data Security & AI roadmap and position the organisation as a forerunner in AI

Data & AI Lead

• Lead the architecture and design of enterprise AI solutions, ensuring they are scalable, secure, resilient and aligned to client business objectives
• Define end-to-end architectures for AI, data and cloud platforms, including LLMs, agentic AI, Retrieval-Augmented Generation (RAG) and intelligent automation capabilities
• Shape technical delivery approaches, lead architectural discovery activities and provide technical oversight across complex AI transformation programmes
• Collaborate with multidisciplinary teams of AI Engineers, Data Scientists, Product Designers and business stakeholders to deliver innovative solutions
• Embed responsible AI, governance, security, risk and compliance requirements throughout the solution lifecycle
• Partner with clients and senior stakeholders to identify AI opportunities, develop technical roadmaps and drive enterprise-wide adoption of AI

Senior AI Architect

• Build and deliver software primarily through AI coding agents such as Claude Code, Codex and other emerging technologies
• Work with Product Managers to understand business problems, explore opportunities and prioritise high-value initiatives
• Design and develop bespoke internal applications, automations and tools
• Translate business requirements and ideas into delivery plans, user stories and technical solutions
• Manage multiple projects, drive progress independently and adapt priorities
• Review, validate and refine AI-generated outputs to ensure secure, scalable and production-ready solutions
• Own the full delivery lifecycle from discovery and design through deployment, monitoring and continuous improvement
• Investigate complex business and technical challenges, identify root causes and develop practical solutions
• Create reusable prompts, workflows and development practices for AI-assisted engineering
• Support the wider engineering function in adopting agentic ways of working

Senior AI Developer

• Design and build production AI systems, including agent-based workflows, tool use, and multi-step reasoning
• Develop and improve models across text, vision, and structured data
• Fine-tune models and apply hybrid ML and LLM approaches
• Work with hosted and self-hosted models
• Contribute to model selection, performance, and cost decisions
• Write clean, maintainable Python
• Contribute to scalable and observable systems
• Design evaluations, measure performance rigorously, and improve systems using real-world feedback
• Use modern AI coding tools while maintaining high standards
• Collaborate with product and engineering teams to deliver high-impact features

• Design and lead end-to-end AI systems from problem framing through production deployment and iteration
• Architect complex agent-based workflows, tool ecosystems, and multi-step reasoning systems
• Make decisions on model selection, fine-tuning, and use of ML, LLM, or hybrid approaches
• Define evaluation frameworks, metrics, and feedback loops for reliability and continuous improvement
• Ensure AI systems are scalable, observable, and robust in real-world environments
• Mentor engineers, review designs, and improve engineering and AI practices across the team
• Drive effective use of AI tooling within the team
• Work closely with product and leadership to shape product direction

Senior AI Engineer

• Build digital products, AI-powered features, agents and automated workflows that solve priority business challenges
• Validate ideas quickly with business stakeholders through AI-prototyped products and solutions
• Use AI-assisted tools such as Claude and/or Copilot from discovery and prototyping through testing, deployment, monitoring and ongoing support
• Build and maintain CI/CD pipelines and deployment automation for cloud-hosted solutions
• Productionise successful prototypes into secure, maintainable internal applications
• Champion effective use of AI to increase engineering productivity and accelerate delivery
• Partner directly with business stakeholders to uncover opportunities, rapidly prototype solutions and iterate based on feedback
• Own the full lifecycle of solutions, including cloud deployment, monitoring and operational support

Senior Software Engineer – AI Products

• Translate real-world network behaviour into structured data and intelligent, AI-driven workflows
• Own the product architecture from MVP to scale across email, WhatsApp, phone and web, on a secure, serverless cloud foundation
• Design AI systems focused on safety, fairness, privacy and transparency
• Ensure recommendations and matching logic are responsible, explainable and free from harmful bias
• Implement best practices for AI governance, model evaluation and responsible data usage as the platform scales
• Understand user requirements and work with the CEO to build the technical strategy and roadmap
• Build hands-on and lead the engineering team as the company grows

Founding CTO, AI Engineer

• Create realistic, challenging coding tasks involving feature implementation and software bug fixes.
• Design tasks that reflect real-world backend engineering scenarios.
• Develop deterministic verifiers that accept reasonable valid solutions and reject incorrect outputs.
• Work with backend technologies such as Java, Node.js, Go, Rust, TypeScript, Python, C++, or similar languages.
• Evaluate code for correctness, reliability, maintainability, and performance.
• Incorporate automated testing and clear validation criteria into coding tasks.
• Identify and account for edge cases, performance bottlenecks, and potential implementation errors.
• Apply secure coding principles and cybersecurity considerations where relevant.
• Refine tasks and verification logic based on project requirements and quality standards.

Backend Software Engineer – AI Training Projects

• Experiment hands-on with new generative image and video models
• Build and refine advanced generative-media workflows using models, prompting, conditioning, automation, and tools such as ComfyUI
• Create model examples, workflows, demos, and visual content demonstrating what developers and creators can build with Runware
• Turn technical experimentation into content for model launches, social media, guides, workflow breakdowns, and creator- and developer-facing channels
• Develop repeatable and automated generation workflows for efficient, scalable, high-quality creative output
• Stay close to new model releases and emerging techniques, rapidly testing them and identifying content opportunities
• Work with Growth, Product, and Engineering to surface use cases, support launches, and share insights from model experimentation and the generative AI ecosystem

Creative Engineer / AI Creative Technologist

• Design, build, and maintain scalable AI architectures and pipelines supporting business requirements
• Operationalise Large Language Models such as GPT, Llama, and Mistral in production environments
• Implement NLP workflows including BERT and topic modelling
• Design and orchestrate autonomous agentic workflows that reason, plan, and execute tasks across multiple tools
• Collaborate with Data Engineers on model deployments, data storage, vector databases, and cloud infrastructure
• Champion and mentor teams and clients on AI-assisted coding and agentic coding workflows
• Provide technical consulting on AI product development and explain the distinction between standard machine learning and agentic AI
• Stay current with modern AI stack developments, synthetic data generation, and Explainable AI
• Work in a multidisciplinary practice with Data Scientists, Data Engineers, and Software Engineers
• Engage with clients to understand their needs and translate them into effective technology outcomes