Vista previa de la oferta
AI Delivery Engineer - Squad Lead
lead · Artificial Intelligence
The AI Team builds production-grade AI solutions across Euronext. We work closely with business and IT teams to identify valuable opportunities and deliver solutions from initial framing and proof of concept through deployment and continuous improvement.
As our portfolio and team grow, we are looking for an AI Delivery Engineer to lead one of our squads. This is first and foremost a hands-on engineering role: approximately 70–80% of your time will be spent designing, building, testing, deploying, and improving AI solutions. The remaining time will focus on backlog management, guiding engineers, stakeholder engagement, use-case framing, and cross-squad coordination.
Your Role
You will be embedded in a small squad, personally contributing to implementation throughout the full delivery lifecycle. You will write production code, solve technical problems, and share responsibility for operating what the squad builds. Alongside this hands-on work, you will help the squad turn ambiguous business needs into practical solutions and deliver with quality, pace, and measurable impact. You will also work with other squad leads and the Head of AI to shape shared engineering practices, reusable components, and technical standards across the team.
What You Will Do
Hands-On Engineering — Approximately 70–80%
Design, implement, test, deploy, and operate production-grade AI solutions, including agentic systems, retrieval-augmented generation pipelines, evaluation capabilities, APIs, and reusable services.
Write and review production code, troubleshoot technical issues, improve performance and reliability, and contribute directly to the squad's delivery commitments.
Own technical work across the lifecycle, from rapid prototypes and architecture decisions through production readiness, monitoring, incident resolution, and continuous improvement.
Make pragmatic engineering decisions that balance business value, delivery speed, security, maintainability, and long-term architecture.
Build reusable components and patterns that solve immediate use-case needs and can be adopted by other squads.
Apply strong software-engineering practices across testing, CI/CD, observability, documentation, security, and AI evaluation.
Keep current with relevant AI technologies and validate them through practical implementation, not research alone.
Squad Leadership and Delivery — Approximately 20–30%
Own and manage the squad backlog and use-case roadmap from framing and proof of concept through deployment and continuous improvement.
Guide engineers through technical decisions, unblock delivery, mentor less experienced colleagues, and support onboarding.
Work directly with business and IT stakeholders to understand workflows, frame opportunities, define scope, and set clear expectations.
Maintain the squad's delivery rhythm, align priorities, surface risks early, and create an open and cohesive working environment.
Coordinate with peer squad leads and the Head of AI on dependencies, shared standards, risks, and cross-squad learning.
Track adoption, quality, user feedback, and business impact, and communicate progress clearly to stakeholders and management.
Support the wider organization's AI transformation by sharing expertise and demonstrating practical solutions.
What We Are Looking For
At least 3–4 years of hands-on experience building and delivering generative AI solutions in a professional environment.
An engineer who wants to spend most of their time building solutions and solving technical problems
A demonstrated record of taking solutions beyond prototypes into production or production-like operation.
Strong software-engineering foundations, including solution design, code review, testing, CI/CD, observability, and secure development practices.
Practical experience with generative AI, such as agentic workflows, tool use, retrieval-augmented generation, prompt design, or evaluation frameworks.
Experience deploying and operating cloud-based workloads; AWS experience is preferred.
Ability to translate ambiguous business problems into clear, feasible technical plans.
Strong leadership skills demonstrated through initiative, influence, technical guidance, mentoring, ownership, or team coordination. Previous formal leadership or people-management experience is not required.
Strong ownership and accountability, with the discipline to communicate progress, risks, and changing assumptions proactively.
Sound prioritization skills and the ability to manage several use cases at different stages.
Clear written and spoken English and the ability to build trusted relationships with technical and non-technical stakeholders.