Senior AI Engineering Lead – Cloud & Production

Ceribell, Inc; United States; On-site; USD 177,000 - 226,000; Full time

Benefits offered by this job

Performance-based incentive

Equity opportunities

Health benefits

401(k) with match

ESPP

Paid time off

Job summary

Ceribell, Inc is seeking a Senior Manager, Applied AI Engineering to drive end-to-end AI projects from definition through production deployment. You will design GCP infrastructure, define architecture, and translate business needs into precise, actionable plans while coordinating with engineering leadership and external partners.

The role requires strong technical execution, experience in cloud infrastructure, and ability to scale AI initiatives across clinical and commercial stakeholders in a

Qualifications

• 8+ years across software engineering, cloud infra, and technical program or product management.
• Active daily use of LLM-based AI tools as core workflow.
• Ability to architect and own GCP infrastructure end‑to‑end.

Responsibilities

• Own AI engineering projects from requirements to production deployment.
• Design GCP infrastructure across environments with CI/CD and security controls.
• Translate business needs into precise specs and challenge scope when needed.
• Lead AI infrastructure rollout and upskill initiatives across the company.
• Develop PRDs and architecture documents for contractors and partners.

Skills

Software engineering

Cloud infrastructure

Technical program management

Product management

LLM tooling

Education

Bachelor's degree

Master’s degree

Tools

GCP

CI/CD pipelines

IAM

Job description

Ceribell, Inc is seeking a Senior Manager, Applied AI Engineering to drive end-to-end AI projects from definition through production deployment. You will design GCP infrastructure, define architecture, and translate business needs into precise, actionable plans while coordinating with engineering leadership and external partners.

The role requires strong technical execution, experience in cloud infrastructure, and ability to scale AI initiatives across clinical and commercial stakeholders in a