Company Overview

Orbis Operations is a technology company that delivers sovereign intelligence and decision capabilities to the United States Government and its allies. We convert complex information and operational systems into decisive outcomes, giving public institutions and critical enterprises the tools to move faster, see clearer, and act first in an increasingly contested world.

We are not a consulting firm and not a systems integrator. Every Orbis team is built around practitioners who have operated at the mission edge, and every engagement is judged on one thing: whether it produces working capability, not slide decks. Solutions forged from experience, that is how we build, and it is how we hire.

Job Summary

Orbis is building the agentic AI capability its mission support operations run on, and the AI Agent Engineer builds and operates it. Sixty percent of this role is common to every AI Agent Engineer at Orbis: designing, building, and deploying the multi-agent workflows behind triage, data retrieval, summarization, reporting, and escalation routing. The remaining forty percent is this role’s focus — owning how clients get support on Orbis products already in the field. This engineer owns the Mission Support Desk (MSD) workflows behind client requests — intake, triage, escalation, and resolution — operates the client-facing surfaces those workflows run on, and holds the response and resolution commitments Orbis makes on deployed products.

Travel: Occasional (up to 10%), which may include international travel.

Key Responsibilities — Common Core (60% of the Role)

Every AI Agent Engineer at Orbis, regardless of focus area, owns the following:

• Design, build, and deploy agentic AI workflows. Architect and ship the multi-agent and automated workflows that run in production: triage, data retrieval, summarization, reporting, and escalation routing.
• Translate in both directions. Explain to non-technical stakeholders what the systems do, where they are reliable, and where they are not, in terms those stakeholders can act on. Equally, take a process owner’s plain-language description of how their work happens and turn it into a workflow specification that holds up.
• Partner with process owners to build what they actually need. Work directly and iteratively with the colleagues who own a process so the resulting capability fits their operation rather than forcing them to fit it. Push back constructively when a stated requirement will not survive contact with production.
• Keep the workflows reliable. Monitor what is running in production, diagnose failures across prompts, tools, data, and orchestration, and resolve them. Know which problems are yours to solve and when to bring in engineering.
• Own the cost of execution. Track what your AI workloads cost to run. Identify where a tighter prompt, a caching layer, or a simple deterministic step delivers the same outcome, and keep those costs defensible as volume grows.
• Set the quality bar for AI-assisted output. Define accuracy standards, human review checkpoints, and escalation criteria for the automated workflows, and build the checks that prove those standards are being met.
• Document what you build. Author and maintain the runbooks and SOPs that allow others to operate and troubleshoot these workflows without you. Nothing lives only in one person’s head.
• Integrate across Orbis products. Work across Catalyst, Pulse, and Discovery, with engineering support where needed, so workflows can access and act on the data they require.
• Deliver the reporting leadership and the team depend on. Build and maintain the outputs behind resolution rate, escalation rate, output accuracy, response time, and employee satisfaction, and turn the Senior Operations Manager’s requirements into structured, recurring reports and data exports.
• Close capability gaps and keep the practice current. Recognize when a need is not served by existing tooling, scope the gap clearly, and either build it or bring it to engineering and product with enough detail to act on. Track developments in agentic AI tooling and enterprise automation platforms, and form a defensible view on what is worth adopting, at what pace, and for which use cases.

Focus Area — Client Experience (40% of the Role)

In addition to the common core above, this role owns what the client sees and touches:

• Build and operate the external-facing interface…