Field AI Platform Lead Engineer

McKinsey & Company; Washington (District of Columbia); On-site; USD 216,700 - 220,000; Full time

Job summary

McKinsey & Company, QuantumBlack division, seeks a Principal Forward Deployed Engineer to deploy and scale an AI platform across cloud and hybrid environments. You’ll work directly with client teams, guiding architectural decisions and ensuring production‑ready systems at scale.

Ideal candidates bring deep engineering experience, knowledge of Kubernetes, CI/CD, and data architectures, and a passion for translating AI strategy into practical, high‑impact solutions.

Qualifications

• Bachelor's degree or higher in computer science, engineering, or related field.
• 8+ years of hands‑on software, platform, or infrastructure engineering with enterprise deployments.
• Strong Python and modern web framework experience.
• Cloud experience with AWS/Azure/GCP, incl. containerization and orchestration.
• Leadership in complex deployments and delivery standards across multi‑stakeholder environments.
• Experience with CI/CD pipelines and infrastructure as code.

Responsibilities

• Lead deployment and scaling of a next‑generation AI platform
• Work directly with clients in their environments
• Bridge software engineering and infrastructure with AI capabilities
• Own platform delivery lifecycle across cloud and hybrid infrastructures
• Lead multi‑workstream deployments across Kubernetes ecosystems
• Collaborate with data scientists and product teams to operationalize AI systems

Skills

Bachelor's degree

Python

React/NextJS

Cloud platforms

Docker

Kubernetes

CI/CD

Terraform

Ansible

PostgreSQL

Education

Bachelor's or Master’s in CS/ML/Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

GitHub Actions

GitLab CI

Job description

McKinsey & Company, QuantumBlack division, seeks a Principal Forward Deployed Engineer to deploy and scale an AI platform across cloud and hybrid environments. You’ll work directly with client teams, guiding architectural decisions and ensuring production‑ready systems at scale.

Ideal candidates bring deep engineering experience, knowledge of Kubernetes, CI/CD, and data architectures, and a passion for translating AI strategy into practical, high‑impact solutions.