[Hiring] AI Agent Engineer @Orbis

Role Description

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 — the cloud platform those workflows run on. This engineer owns the footprint across GCP, Cloudflare, and Azure, manages it as code, and holds its networking, security posture, and run cost to a standard that survives scrutiny as volume grows.

Travel: Occasional (up to 10%) to McLean, VA or team offsites as needed

Key Responsibilities

• 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.
• Partner with process owners to build what they actually need.
• Keep the workflows reliable.
• Own the cost of execution.
• Set the quality bar for AI-assisted output.
• Document what you build.
• Integrate across Orbis products.
• Deliver the reporting leadership and the team depend on.
• Close capability gaps and keep the practice current.

Focus Area

• Design, deploy, and maintain the Orbis cloud footprint across GCP, AWS, Cloudflare, and Azure.
• Define and manage that footprint as infrastructure as code.
• Own networking, identity, and secrets handling for agent workloads.
• Hold the security posture of the platform.
• Track and control platform run cost across compute, inference, storage, and egress.
• Build and maintain the deployment and release path — CI/CD, environment promotion, rollback.

Qualifications

• 5 years of proven experience translating user requirements into wireframes, workflows, and such.
• 1-year proven experience utilizing Claude or similar commercial offering to build AI agents.
• Demonstrated experience building a functioning multi-agent workflow.
• Practical command of prompt engineering, including retrieval-augmented generation (RAG) and tool or function calling.
• Proven ability to explain technical work to non-technical audiences.
• Demonstrated ability to elicit requirements from stakeholders.
• Ability to troubleshoot agent workflows built on platforms such as Claude, GPT-class models, LangChain, AutoGen, or CrewAI.
• Working proficiency with APIs and sufficient scripting ability.
• Sound judgment about model output.
• Strong written communication.
• Hands-on production experience with at least one major cloud platform (GCP, Azure, or Cloudflare).
• Practical experience managing infrastructure as code using Terraform, Pulumi, or an equivalent.
• Working command of cloud networking, identity, and secrets management.

Desired Qualifications

• 5-7 years experience in software development.
• Experience coding using Python.
• Kubernetes or serverless runtimes at production scale.
• FinOps or formal cloud cost management practice.
• Owning CI/CD pipelines end to end.
• Prior work as a solutions consultant, technical program manager, or in a product-adjacent role.
• Monitoring, evaluation, or observability tooling for AI systems in production.
• Designing SOPs or escalation frameworks.
• Working fluency with Claude, Copilot, or Cursor.
• Operating within or supporting a government or defense program.
• A track record of coming up to speed quickly on unfamiliar systems.

Physical Requirements

• Prolonged periods of sitting at a desk and working on a computer.
• Participation in virtual and in-person meetings.
• Ability to attend planned meetings and/or work in classified spaces for extended periods.
• Travel: Occasional (up to 10%) to McLean, VA or team offsites as needed.

Benefits

• Real ownership over outcomes that matter.
• Competitive retirement matching.
• PTO policy that encourages real time off.
• Comprehensive benefits package designed to meet diverse needs.