Chief Technology Officer

Our client is developing an agentic operating system for global trade. The platform provides exporters with a single workspace to manage customer relationships, product specifications, orders, compliance evidence and shipments. AI-powered agents coordinate operational workflows and follow up activities across partners, while people retain control over decisions and commercial approvals. The business is moving from a tested platform build into production deployment with paying customers. Current progress includes: - Paid pilots across 11 countries. - Five alpha pilots. - More than 223 passing automated tests. - Initial trade corridors connecting Asia with the EU and UK. The business is now seeking an exceptional technical leader to take its AI agent infrastructure into production and support its next stage of commercial growth. We are seeking an experienced, hands-on Fractional CTO who combines deep AI engineering expertise with a proven track record of building and scaling production software platforms. This is not an advisory-only position. You will take ownership of the technical direction, architecture and delivery of the platform, with a particular focus on turning agentic AI capabilities into reliable, secure and scalable production systems. You will work directly with the founders, shape the engineering roadmap and establish the technical foundations needed to support commercial growth. The ideal candidate is equally comfortable designing system architecture, fine-tuning language models, building agent workflows and reviewing or writing production code. Key Responsibilities 1. Technical Leadership & Architecture - Own the technical direction and architecture of the platform. - Define the engineering roadmap in collaboration with the founders. - Establish technical standards, development practices and production readiness criteria. - Build a scalable platform architecture supporting multiple customers, partners and workflows. 2. AI Agents & Production Engineering - Lead the transition of AI agents from tested builds into production systems. - Design and implement durable, long-running agents capable of managing workflows over extended periods. - Build agent capabilities including retries, state management, resumption following partner responses and dynamic re-planning when specifications, dates or rules change. - Develop tool-use capabilities, retrieval systems, multi-model routing and agent orchestration. - Establish robust evaluation frameworks and release gates for model-driven features. 3. AI Safety, Governance & Security - Embed security and governance directly into the agent architecture. - Implement scoped data access, least-privilege permissions and prompt-injection defences. - Ensure agent-generated commercial proposals and actions require appropriate human approval. - Maintain a complete audit trail of agent activity, data access and proposed actions. - Establish observability, reliability and incident management practices. 4. Platform Engineering & Infrastructure - Own the development of a secure, multi-tenant SaaS platform. - Implement PostgreSQL row-level security, workspace entitlements and partner workspace permissions. - Define and manage APIs, data models, integrations and platform extension points. - Establish CI/CD, automated testing, monitoring and rollback processes. - Manage performance, infrastructure costs and latency budgets at workspace level. 5. Engineering Team Development - Establish the engineering organisation and development processes as the business scales. - Recruit, lead and mentor a small engineering team as funding allows. - Maintain a hands-on contribution to architecture, coding, code reviews and technical problem-solving. Required Experience & Technical Skills Production AI & LLM Engineering - Proven track record of shipping LLM-powered systems into production, rather than simply building prototypes. - Strong hands-on experience with LLM tool use, agents, retrieval, evaluation frameworks and failure handling. - Practical experience fine-tuning models using LoRA, SFT and DPO. - Experience with Unsloth and NVIDIA NeMo, including serving fine-tuned models through NVIDIA NIM. Agent Infrastructure - Experience with Model Context Protocol (MCP). - Multi-model routing and orchestration. - Durable workflow engines and long-running agent processes. - Experience building reliable systems that can recover, resume and adapt to changing inputs. Full-Stack & Platform Engineering - Strong TypeScript and JavaScript skills. - React and Next.js. - Node.js and Python. - PostgreSQL and Supabase. - REST and GraphQL APIs. - Cloud infrastructure, CI/CD and automated testing. Platform Architecture & Security - Experience building multi-tenant SaaS platforms. - Strong understanding of permissions, data isolation and workspace-level access controls. - Experience designing APIs, extension points and versioned data models. - Security-first engineering, observability and production reliability. Technical Leadership - Previous experience leading engineering in a startup environment, ideally at Seed or Series A stage. - Ability to operate effectively in a fractional or part-time CTO capacity. - Comfortable working directly with founders and translating business priorities into technical delivery. - A hands-on engineering mindset: someone who still writes code and takes ownership of delivery. Role & Remuneration - Engagement: Fractional / part-time CTO. - Location: Remote, with an Ireland base preferred. - Time commitment: Days per week to be agreed. - Compensation: Competitive day rate, with potential equity participation. - Start date: By mutual agreement.