Director of Software Engineering, Analytics

Planet•Arlington, VA

16h•$180,700 - $225,900•Hybrid

About The Position

As the Director of Engineering, Analytics, you will lead, staff, and scale the engineering organization that builds Planet’s analytics: the models and pipelines that turn daily satellite imagery into answers about what changed at a site, what is moving in a port, and what is being built across a country. These analytics power Planet’s dual-use products such as Global Monitoring Service (GMS) and Maritime Domain Awareness (MDA) for defense use cases, and are expanding into commercial and civil government use through the same models and platform. You will lead engineering managers and engineers across Denver, Washington DC, remote North America, and Europe. You will be responsible for building the team, the plan, the delivery, and the operating model and will report to the VP of Technology. This is a build role: the organization is moving from hand-built detectors to foundation-model-based methods, scaling from hundreds of monitored sites to thousands, and operating across classified and unclassified environments. This is a full-time, hybrid role which will require you to work from our Denver or Washington DC office 3 days per week. This role requires US person status and the ability to obtain and hold a US government security clearance.

Requirements

8+ years of experience in software or machine learning engineering, with a focus on computer vision, geospatial analytics, or high-scale data systems.
6+ years of experience leading engineering teams, including direct experience managing engineering managers and growing an organization through a scaling step.
Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (or equivalent practical experience).
Track record of shipping machine learning, computer vision, or geospatial analytics into production and owning the results.
Direct experience leading engineering work governed by International Traffic in Arms Regulations (ITAR) and Export Administration Regulations (EAR), with cleared and uncleared staff on the same team.
Success pairing with a solid technical lead or architect who owned technical direction while you owned people, plan, and delivery.
Ability to write a clear plan and a clear status report, and to drive delivery against dated commitments.
US person status and an active US government security clearance, or eligibility to obtain one upon hire (TS/SCI preferred).

Nice To Haves

Master’s degree or Ph.D. in Computer Science, Machine Learning, Remote Sensing, or a related technical discipline.
Experience leading a computer vision team through a shift from task-specific models to foundation models or embeddings.
Experience delivering analytics into classified, air-gapped, or sovereign cloud environments (e.g., AWS GovCloud/C2S) and knowing what breaks.
Experience integrating an acquired team or merging two engineering groups.
Domain knowledge in Synthetic Aperture Radar (SAR), maritime, or activity-based intelligence work.
Defense or intelligence customer exposure, including working directly with operators and analysts.

Responsibilities

Develop and execute a talent strategy supporting our product roadmap.
Build a staffing plan and develop, recruit, and hire talent accordingly.
Manage performance directly and build bench depth to limit single points of failure.
Turn program commitments into dated, owned work and report status plainly, including slippage.
Own the analytics side of the interface with the Global Monitoring Service (GMS) and Maritime Domain Awareness (MDA) application teams and deliver against the shared quality and latency targets.
Define and execute a strategy for developing models that serve classified and unclassified environments.
Serving the needs of customers in classified spaces while keeping the models themselves dual-use.
Build a strategy for how to evolve our existing portfolio of analytics to stay up to date with the latest developments in foundation models.
Know what each pipeline costs per site and per square kilometer, and plan for the ten-times scale-up that contract growth implies.