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Airis Labs transforms user-generated content into actionable field intelligence for government agencies worldwide. The platform uses multimodal AI tools to extract clarity from fragmented, unstructured media, empowering frontline analysts with rapid insights.
In this role, you will serve as the bridge between Airis Labs and its government clients. You will work closely with clients in the field to understand their intelligence questions and translate operational needs into effective workflows. Your responsibilities include:
• Understanding the core intelligence challenges clients face and designing workflows within Airis to address them
• Driving rapid first value on-site, establishing credibility and trust from day one
• Identifying new use cases and opportunities to expand value throughout client accounts
• Enabling end-users and driving adoption across the client organization
• Acting as an internal domain expert, bringing field insights back to Airis to inform product priorities and strategy
• Collaborating with Product, R&D, and commercial teams to translate client needs into scalable, repeatable solutions
• Traveling approximately 50% of the time to work alongside clients on-site
This is a hands-on role requiring resourcefulness, a builder's mindset, and a genuine commitment to making things work in complex operational environments.
REQUIREMENTS:
• Intelligence background: military, government, or equivalent experience. You understand intelligence workflows and can translate fragmented information into actionable insights.
• Client-facing experience: proven track record working directly with external clients, building trust, and navigating multiple stakeholders.
• Relevant experience: you have held this role or a similar position in more than two different environments.
• Builder mindset: hands-on, resourceful, focused on execution and problem-solving.
• Willingness to travel ~50% and spend significant time working on-site with clients.
STRONG PLUSES:
• OSINT experience: ability to build a complete picture from fragmented open-source information and understanding of where open-source intelligence works and where it doesn't.
• Additional languages.
• AI/automation experience: you have built automations, agents, workflows, or small tools to solve real problems.
