Field-Facing AI Deployment Architect

McKinsey & Company; San Francisco (CA); On-site; USD 216,700 - 220,000; Full time

Job summary

McKinsey & Company is seeking a Principal Forward Deployed Engineer to lead the deployment and scaling of a next-generation AI platform, embedding with clients in real-world environments. You will drive multi-workstream deployments across cloud and hybrid infrastructures, shaping delivery practices and tooling.

You will collaborate with data scientists, ML engineers, designers, and technologists to operationalize AI systems, contribute to product evolution, and mentor engineers within a global

Qualifications

• Bachelor’s or master’s degree in CS, ML, applied statistics, mathematics, engineering, or related field.
• 8+ years hands-on software/platform/infrastructure engineering with enterprise-scale experience.
• Proficiency in Python and modern web frameworks; strong cloud and containerization experience.

Responsibilities

• Lead deployment and scaling of a next-generation AI platform across cloud and hybrid infrastructures.
• Work directly with clients, embedded in their environments, guiding complex deployments.
• Own the platform delivery lifecycle across engagements and set direction for multi-workstream deployments.

Skills

Python

React/NextJS

Docker

Kubernetes

Cloud platforms

CI/CD

Infrastructure as Code

Databases (PostgreSQL/graph databases)

AI-native platform concepts

Problem solving

DevSecOps

Observability & compliance

Travel readiness

Education

Bachelor’s/Master’s in CS/ML/AI/Engineering or related field

Tools

Docker

Kubernetes

GitHub Actions

GitLab CI

Terraform

Ansible

Helm

Job description

McKinsey & Company is seeking a Principal Forward Deployed Engineer to lead the deployment and scaling of a next-generation AI platform, embedding with clients in real-world environments. You will drive multi-workstream deployments across cloud and hybrid infrastructures, shaping delivery practices and tooling.

You will collaborate with data scientists, ML engineers, designers, and technologists to operationalize AI systems, contribute to product evolution, and mentor engineers within a global