Our client is a leading pan-European market infrastructure, operating regulated financial markets and delivering innovative technology solutions across Europe. As part of its growing AI Team, we are looking for a hands-on AI Delivery Engineer to lead an AI delivery squad.
This is primarily an engineering role: 70–80% of your time will be dedicated to designing, building, deploying, and continuously improving production-grade AI solutions. The remaining time will focus on delivery coordination, technical guidance, backlog management, and stakeholder alignment.
🎯 Key Responsibilities
- Design, build, test, deploy, and operate AI solutions, including agentic workflows, RAG pipelines, AI evaluation capabilities, APIs, and reusable services.
- Own the full technical lifecycle, from use-case framing and rapid prototyping to production deployment, monitoring, incident resolution, and continuous improvement.
- Write and review production code while applying best practices in testing, CI/CD, security, observability, and documentation.
- Manage the squad backlog and roadmap, ensuring clear priorities, delivery momentum, and proactive risk management.
- Guide and mentor engineers, support technical decisions, and remove delivery blockers.
- Collaborate with business and IT stakeholders to turn complex needs into pragmatic, scalable AI solutions.
- Track solution quality, adoption, user feedback, and business impact; share progress with key stakeholders.
👤 Profile & Technical Requirements
- 3–4+ years of hands-on experience delivering Generative AI solutions in a professional environment.
- Practical expertise in LLMs, agentic systems, RAG, tool calling, prompt engineering, and/or AI evaluation frameworks.
- Proven experience bringing AI solutions beyond proof of concept into production or production-like environments.
- Strong software-engineering foundations, including solution design, code review, automated testing, CI/CD, observability, and secure development.
- Experience deploying and operating cloud workloads; AWS experience is a strong advantage.
- Strong ownership, prioritisation, and problem-solving skills, with the ability to manage several use cases at different stages.
- Demonstrated technical leadership through mentoring, coordination, or influence; formal people-management experience is not required.
- Fluent written and spoken English, with excellent communication skills for technical and non-technical stakeholders.