Fractional CTO - Cloud & AI Operations (AWS/GPU, Computer Vision)

This is not a software feature-development role. We’re hiring a relationship-forward, externally-facing technical leader who can represent BrandPulse in partner/customer conversations and personally own our AWS/GPU cloud operations for a computer-vision product.

You won’t be the primary model builder, we already have an AI Engineer. Your job is to lead the technical function, guide the team, and ensure our cloud/GPU environment is reliable, secure, and cost-controlled.

Location: Remote (US time zones preferred)
Type: Paid fractional/part-time (hourly or retainer) → targeted full-time in Q2/Q3
brandpulsemedia.ai

Overview
BrandPulse builds AI + computer vision technology for sports visibility and sponsorship analytics. We’re hiring a Fractional CTO to own our AWS infrastructure, GPU compute operations—and to help guide the team as we scale.

Non-negotiable: You’ve owned production AWS operations (deployments, monitoring/alerting, incident response, cost controls) and have hands-on AWS GPU experience.

Why this role

This is a front-seat opportunity for a senior technical leader who wants CTO-level ownership—starting fractional while we ship key milestones, with a targeted ramp to full-time as we grow.

What you’ll own

1) Cloud & AI operations on AWS (core)

• Create and manage AWS environments (dev/stage/prod), set up guardrails, and keep the platform stable
• Own deployments, CI/CD, monitoring/logging, alerting, backups, and incident response
• Establish cost controls (budgets, alerts, optimization) and manage GPU spend proactively
• Own AWS security & connectivity: IAM roles/policies, secrets management, VPC/security groups, audit trail, least-privilege access

2) AWS GPU operations (core)

• Own GPU compute strategy on AWS: instance/service selection, provisioning, scaling approach, utilization, and reliability
• Support production inference/training operations with runbooks, observability, and rollback plans
• Optimize GPU cost/performance and ensure workloads “work in production”

3) Technical leadership + external communication (core)

• Lead technical demos and architecture reviews with external stakeholders (partners/customers)
• Explain roadmap, tradeoffs, and system design clearly to non-technical audiences
• Lead a small senior team (Full-Stack Engineer + AI Engineer) and set lightweight standards (code review, documentation, release process)

4) Computer vision context (leadership, not primary development)

• Understand CV/ML concepts well enough to guide the AI Engineer, make pragmatic decisions, and ensure production readiness
• Align model work with infrastructure realities (latency, reliability, cost, monitoring)

Must-have experience

• Deep AWS + DevOps ownership in production (not just “familiar with AWS”).
• Proven experience managing cloud cost and reliability tradeoffs.
• AWS security/networking fundamentals (IAM/VPC/secrets).
• Operating GPU workloads on AWS (inference and/or training).
• Ability to lead and execute in an early-stage environment.

Nice to have

• MLOps experience (model versioning, deploy/rollback, monitoring).
• IaC (Terraform/CDK/CloudFormation), containers/orchestration.
• Prior startup leadership (0→1 or early scale).

Compensation

• Fractional/part-time to start (scope + weekly hours agreed upfront).
• Targeted to full-time in Q2/Q3.
• Equity included.

Pay: From $100,000.00 per year

Work Location: Remote