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Agentic GEOINT Mission Management Lead

Job in Denver, Denver County, Colorado, 80202, USA
Listing for: Voyager Technologies
Full Time position
Listed on 2026-07-31
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Business & Operations
Job Description & How to Apply Below

Agentic GEOINT Mission Management Lead

Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space.

Forge the future:
Join Voyager Technologies

The future belongs to those who build it. At Voyager Technologies, we're building technologies that protect lives, expand frontiers and prepare us for what's next. And we're doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.

You'll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We're a company of doers, thinkers and builders, united by purpose and grounded in reality.

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person, forge the future with Voyager.

Job Summary:

We are seeking an Agentic GEOINT Mission Management Lead to lead the technical effort building Voyager's Agentic Mission Management platform — an AI-native system that lets intelligence operators task and orchestrate large, heterogeneous satellite constellations through natural conversation instead of manual planning tools. In this role, you will own the technical vision and hands-on execution for a platform that turns operator intent into physically valid, explainable, executable collection plans — and matures it from working prototype to accredited operational capability.

You will sit at the intersection of GEOINT tasking tradecraft, collection orchestration, and agentic AI. This role is a fit for someone who has lived the tasking-to-dissemination cycle and gets impatient with monolithic, opaque, manual planning workflows — who knows that the target deck now changes by the hour while constellations have grown from a handful of exquisite assets to hundreds of government, commercial, and allied satellites, and who wants to see their agents task real sensors against real physics, not just push text around.

The work also involves decomposing the judgment of collection managers and mission planners into agent definitions, tool integrations, scheduling and astrodynamics couplings, and evaluation suites.

You will be joining a specialized group within our Advanced Technology Development organization responsible for building Voyager's Agentic Mission Management platform — the AI-native system that translates human intent into mission management action. We design agentic AI systems that pair deeply with orbital mechanics, sensor models, and live mission data so that physical feasibility, explainability, and operator trust are built into every recommendation from the very first request — and so that autonomy grows deliberately, as the system earns it.

Responsibilities:
  • Serve as Principal Investigator (PI) for the Agentic Mission Management effort — own the technical vision, technical roadmap, and execution; represent the work to Intelligence Community and national security space customers; and carry it from working prototype to fielded, accredited capability.
  • Lead the design of an agentic architecture in which an AI orchestrator calls mission capabilities as tools, in whatever order the mission needs.
  • Design, implement, and deploy production-ready AI agents (using state-of-the-art models from Google, OpenAI, etc) that translate operator intent expressed in plain language into structured collection requests and physically valid collection plans, checked against real orbital mechanics, sensor phenomenology, and access constraints — not just geometry.
  • Build explainability and human-on-the-loop trust into the platform: every AI recommendation traceable, auditable, and defensible to the operator, with autonomy that expands as the system demonstrates reliability.
  • Develop and maintain Model Context Protocol (MCP) servers that expose mission systems — target decks and collection requirements,…
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