Experteer Overview In this role you will lead the deployment and scaling of a next-generation AI platform that connects strategy to execution through analytics and AI. You will work directly with clients in cross-functional settings, shaping delivery across cloud and on-prem environments. You’ll own the platform delivery lifecycle, drive multi-workstream deployments, and mentor teams to raise quality and delivery standards. This is a hands-on, client-facing engineering and product-influence role at the intersection of software, infrastructure, and AI.Compensaciones / Ventajas
- Lead end-to-end platform delivery lifecycle for enterprise-scale deployments
- Execute multi-workstream deployments across cloud and hybrid infrastructures (AWS, Azure, GCP)
- Architect and guide complex deployments; influence architecturaldirection
- Build and enforce delivery standards, automation, and tooling
- Collaborate with data scientists, ML engineers, designers, and technologists
- Mentor engineers and contribute to team development and quality improvements
- Ensure production-readiness, validation, and handovers for AI-enabled platforms
- Engage with senior technical stakeholders and contribute to client-facing delivery discussions




- Provide feedback to product teams to shape platform evolution
- Operate in regulated environments and support secure deployment practicesResponsabilidades
- 8+ years of hands-on software, platform, or infrastructure engineering experience
- Strong full-stack engineering with Python and modern web frameworks (React, NextJS or equivalent)
- Experience deploying cloud-based systems (AWS, Azure, or GCP) with Docker and Kubernetes
- Hands-on operating production systems; Kubernetes architectureand lifecycle management
- Experience leading complex deployments and setting delivery standards across multiple stakeholders
- CI/CD and Infrastructure as Code experience (GitHub Actions, GitLab CI, Terraform, Ansible, Helm)
- Relational databases (PostgreSQL) and familiarity with graph databases (Neo4j)
- Experience with AI-native platform concepts, model integration, and multi-agent workflows (plus)
- DevSecOps, security, and networking fundamentals; observing and securing environments
- Willingness to travel; strong client-facing communication and workshop facilitationRequisitos principales
- competitive salary
- comprehensive benefits package

📌 Principal Forward Deployed Engineer - Quantumblack, Ai By Mckinsey (Madrid)
🏢 McKinsey u0026
📍 Madrid