Vice President Defense and Intelligence Engineering

Planet•Denver, CO

10d•Hybrid

About The Position

As the Vice President of Defense and Intelligence (D&I) Solutions Engineering, you will lead, scale, and direct the software engineering organization responsible for building Planet’s end-to-end dual-use products and applications. You will own the technical architecture, systems development, and operational delivery of flagship dual-use products—such as Global Monitoring Service (GMS), Marine Domain Awareness (MDA), automated change detection feeds, and agentic workflows. In this executive engineering role, you will lead multi-disciplinary teams across software, architecture, AI/ML, analytics, and forward deployed engineering. You will partner directly with Product Management, Core Platform Engineering, and Executive Leadership to transform raw satellite imagery and API services into scalable, mission-critical dual-use software solutions. You will oversee system availability, performance SLAs, and ITAR-compliant deployment pipelines, serving as the senior engineering authority for Planet’s defense and intelligence software portfolio. Ideal candidates are visionary engineering leaders passionate about delivering impactful geospatial solutions. This is a full-time, hybrid role which will require you to work from our Denver, CO office 3 days per week.

Requirements

15+ years of experience in software engineering and systems architecture, with a focus on high-scale data, computer vision, or geospatial applications.
8+ years of direct experience leading and scaling multi-disciplinary engineering organizations (software, data/ML, platform, and cloud infrastructure).
Direct experience managing engineering teams, software build pipelines, and data handling governed by International Traffic in Arms Regulations (ITAR) and Export Administration Regulations (EAR).
Track record of architecting, building, and operating end-to-end dual-use or defense software applications (such as domain awareness, automated change detection, or spatial monitoring platforms) at scale.
Active high-level government security clearance, or eligibility to obtain top-secret clearance upon hire.
Deep technical expertise in distributed cloud architectures, high-throughput data processing pipelines, API infrastructure, and machine learning model integration.
Ability to drive software delivery metrics, maintain high operational availability/SLAs, and establish rigorous engineering practices.
Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Data Science, or a related technical field (or equivalent practical experience).

Nice To Haves

Master’s degree or Ph.D. in Computer Science, Software Engineering, Machine Learning, or a relevant technical discipline.
Direct engineering experience building foundation models for remote sensing use cases, agentic platforms, or automated tip-and-cue execution loops.
Background in developing software for secure government environments, air-gapped systems, or sovereign cloud deployments (e.g., AWS GovCloud/C2S).
Experience in multi-sensor data fusion workflows, including optical satellite imagery and Synthetic Aperture Radar (SAR).

Responsibilities

Lead, mentor, and scale multi-disciplinary software engineering teams (software, data/ML, platform, and infrastructure) tasked with building and maintaining end-to-end dual-use products like Global Monitoring Service (GMS) and Marine Domain Awareness (MDA).
Define the software architecture, data models, and technical standards required to deliver high-throughput geospatial analytics, real-time alerting, and automated detection platforms at scale.
Oversee engineering development standards and deployment pipelines to ensure full technical compliance with International Traffic in Arms Regulations (ITAR) and Export Administration Regulations (EAR).
Partner with Product Management to translate high-level market vision and defense mission requirements into scalable engineering roadmaps, system designs, and execution sprints.
Direct the technical integration of advanced machine learning models, analytics, and agentic workflows into Planet's dual use product stack.
Drive software engineering metrics, system reliability, low-latency processing, and secure cloud deployment architectures across commercial and sovereign environments.