About this role
The team builds pioneering platforms for electric utilities using satellite intelligence to unify vegetation, asset, storm, and wildfire data. This role scales the AI Data Ops function by sourcing, processing, and annotating satellite and remote sensing imagery that powers machine learning models. Operating at the intersection of strategy, operations, vendor management, and data science delivery, this person establishes an automation-first, process-driven operating model.
Created to reduce operational complexity and build a repeatable operating system, the position requires solving ground-level problems while designing long-term processes, playbooks, and automation. A successful candidate brings a high-agency mindset, extensive experience in program management or business operations within startups, and a strong capability in data-driven decision making and vendor optimization.
What you will do
- Identify repetitive manual workflows across annotation, quality assurance, imagery processing, and reporting to drive automation through internal tooling, scripting, or AI-assisted methods.
- Run structured program governance including milestones, risk logs, and status cadences across complex cross-functional initiatives.
- Own a cost-efficiency roadmap that monitors vendor spend, tooling costs, rework expenses, and capacity utilization with clear metrics.
- Design and maintain performance scorecards and SLAs for third-party imagery and annotation vendors while handling renewals and escalations.
- Serve as a connective tissue across managers to surface shared operational problems and establish organization-wide standard operating procedures.
- Build dashboards and reports tracking throughput, accuracy, vendor performance, and cost efficiency to provide leadership with actionable insights.
- Manage budgets across data sourcing, annotation operations, and vendor contracts while identifying optimization opportunities.
What you need
- Bring 5 or more years of professional experience spanning program and project management, business operations, or management consulting.
- Demonstrate exposure to automation, operational scaling, vendor management, and cost optimization.
- Show a proven track record of building metrics and automation programs entirely from scratch.
- Possess comfort with data to independently build and defend dashboards and business cases.
- Exhibit strong written and verbal communication skills for cross-functional collaboration and external partner conversations.
- Demonstrate hands-on experience working in a fast-paced startup environment.
- Have prior experience managing external vendors and negotiating service level agreements.
Nice to have
- Prior exposure to GIS, geospatial, imagery, or annotation-heavy operations
- Experience standing up automation, RPA, or AI tooling programs
Skills and tech stack
Questions candidates ask
What team does this role belong to?
This role sits within the AI Data Ops team, which is responsible for sourcing, processing, and annotating satellite and remote sensing imagery that powers AI and machine learning models.
What kind of background is required for this position?
Candidates need at least 5 years of experience spanning program or project management, business operations, or management consulting, along with hands-on startup experience.
What are the primary focuses of this job?
The focus is on driving automation for manual workflows, building structured program governance, owning vendor performance scorecards, and managing cost-efficiency roadmaps.