Own the orchestration layer: planning, tool selection, state and memory, retries, partial failure, and termination behavior.
Design and own retrieval end to end — chunking, embedding, indexing, ranking, and the query-time behavior that decides answer quality.
Build the provenance and citation paths that let a user see how a conclusion was reached, and treat unexplainable output as a defect rather than a limitation.
Own the evaluation infrastructure for agent quality — accuracy, groundedness, explainability, latency, and cost — and set the standard other engineers write cases against.
Integrate model providers and third-party tools behind stable internal interfaces, and instrument agents so quality regressions and cost anomalies surface before a customer finds them.
Partner with research engineers to productionize validated results, and mentor engineers moving into AI work from a conventional software background.
Travel up to 15% for customer engagement, integration support, and team collaboration.
Required Qualifications
4+ years of professional software engineering experience, including 2+ years building LLM-backed or agentic systems in production
Bachelor's degree in Computer Science, a related technical field, or equivalent professional experience
Strong programming skills in Python and/or TypeScript, with substantial production code in at least one
Deep practical experience with retrieval-augmented generation — embeddings, vector search, chunking strategy, ranking, and the failure modes of each
Demonstrated experience building and debugging multi-step, tool-using agents, whether on a framework or from primitives
Proven rigor about evaluation, including harnesses that measured whether an AI change actually improved anything
Willingness to travel up to 15%
Desired Qualifications
Experience with knowledge graphs, ontologies, entity resolution, or information extraction
Experience running open-weight models in constrained or disconnected environments where a hosted API is not an option
Experience with production observability and cost control for model-backed workloads
Familiarity with OSINT, intelligence, or research workflows and the accuracy and provenance expectations that come with them
Experience mentoring engineers into AI work from a conventional software background
Open-source contributions, publications, or academic collaboration in applied AI
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 within the specified work regions
Travel: Up to 15% for customer engagement, integration support, and team collaboration.
Orbis Benefits
Beyond the opportunity to work alongside practitioners who have operated at the mission edge, joining Orbis means real ownership over outcomes that matter; the chance to build technology that gives the United States Government and its allies a genuine decision advantage, not just another dashboard. From competitive retirement matching to a PTO policy that encourages real time off, we're committed to creating an environment where our team can do their best work and still have a life outside of it.
Our comprehensive benefits package is designed to meet the diverse needs of our employees and their families. A full list of benefits is shared with candidates following an initial conversation with our HR team, so you'll have a clear picture of the support and resources available to you as part of the Orbis team.
Orbis Locations
Orbis works in whatever arrangement the mission requires. Depending on the role, that might mean five days a week on a customer site, full-time in one of our offices, a hybrid schedule, or fully remote work; our team is spread across 25 states and four countries to match. We make sure every team member has the tools and access needed to do the work, wherever that work happens.
Travel is common across many Orbis roles, particularly those supporting customer missions in the field.
Orbis is headquartered in McLean, VA, with additional office locations in Taipei, Taiwan, and Canberra, Australia.
Orbis is an Equal Employment Opportunity employer. We are committed to providing a work environment free of discrimination and harassment, and we make employment decisions based on merit,
qualifications, and business need. Orbis does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, genetic information, or any other status protected by applicable law.
Orbis complies with all applicable equal opportunity and non-discrimination laws in every jurisdiction in which we operate. Reasonable accommodation is available to applicants and employees with disabilities upon request.
