Experteer Overview
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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 / Incentivos
• 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 architectural direction
• 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 practices
Responsabilidades
• 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 architecture and lifecycle management
• Experience leading complex deployments xqbhyrx 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 facilitation
Requisitos principales
• competitive salary
• comprehensive benefits package

📌 Principal Forward Deployed Engineer - QuantumBlack, AI by McKinsey (Madrid)
🏢 McKinsey u0026
📍 Madrid