The Role

AiDASH is looking for a high-agency Program Manager to help scale our AI Data Ops function: the team responsible for sourcing, processing, and annotating the satellite and remote sensing imagery that powers our AI/ML models.

This role is a new addition to the leadership team, created specifically to bring an automation-first, numbers-backed, process-driven operating model to how Ops runs . This role is designed to reduce operational complexity over time, not to manage individual queues or projects indefinitely. You will sit at the intersection of strategy, operations, vendor management, and data science delivery, helping AI Data Ops evolve from a fast-scaling function into a well-designed, repeatable operating system.

You will need to zoom in to solve real problems on the ground — a stuck vendor SLA, a high priority escalation, a broken handoff — and zoom out to design the processes, playbooks, and automation that stop the same problems from recurring.This is a high-visibility, build-from-scratch role: you'll be judged on the systems and habits you install, not just the projects you close.

How You’ll Make an Impact:

Automation & AI-native ways of working

• Identify repetitive, manual workflows across annotation, QA, imagery processing and reporting, and drive their automation — via internal tooling, scripting, RPA, or AI-assisted workflows.

• Build and own the automation roadmap and drive it seamlessly across the team

Program & project management

• Run structured program governance (milestones, RAID logs, status cadence) across cross-functional initiatives that no single manager owns end-to-end.

• Bring discipline — timelines, ownership, dependencies — to all team initiatives

Cost reduction

• Own a cost-efficiency roadmap for Ops: vendor spend, tooling spends, rework/error costs, and capacity utilization.

• Build the business case and track savings with real numbers- Clear visible impact

Vendor performance frameworks

• Design and own scorecards/SLAs for imagery, annotation and other third-party vendors.

• Run regular vendor performance reviews and own escalation/renewal/replacement decisions in partnership with managers.

Cross-functional ownership & data ownership

• Serve as the connective tissue across all managers and leads — surfacing shared problems (tooling, process, vendor etc) that no single manager can fix alone.

• Own org-wide SOP creation and the dashboard/metrics layer (throughput, quality, SLA, utilization) so every manager works off the same numbers.

Enable leadership with insight and structure

• Build dashboards/reports tracking throughput, accuracy, vendor performance, and cost efficiency; define KPIs that drive decisions on quality, capacity, and cost

• Manage budgets across data sourcing, annotation ops, and vendor contracts, identifying cost-optimization opportunities

• Translate ambiguous problems into structured, actionable plans

What We're Looking For:

• 5+ years of experience spanning program/project management, business operations, or management consulting — ideally with exposure to automation, Ops, vendor management and cost optimization.

• A genuine track record of building metrics/automation programs from scratch — not just running ones someone else designed.

• Comfort with data: you should be able to build and defend a dashboard or a business case yourself, not just commission one.

• Strong written and verbal communication — you'll be the face of Ops in external conversations.

• Experience managing external vendors/partners and negotiating SLAs.

• Bonus: prior exposure to GIS, geospatial, imagery, or annotation-heavy operations; experience standing up automation/RPA/AI tooling programs (This is not mandatory)

• Must-have: hands-on experience working in a startup environment.

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.