Senior Software Engineer, Agentic AI

Orbis; United States; Hybrid; USD 150,000 - 230,000; Full time

Job summary

Orbis is seeking a senior engineer to own the agentic systems at the center of Orbis AI—the orchestration, planning, retrieval, and tool-use machinery behind the Agent Catalog and the OSINT Agent Harness.

You will build agents that endure real mission workloads, focusing on correctness, explainability, cost, and scalable behavior, with travel for customer engagement up to 15%.

Qualifications

• 4+ years of professional software engineering experience, including 2+ years building LLM-backed or agentic systems in production.
• Bachelor's degree in CS or related technical field, or equivalent experience.
• Strong programming skills in Python and/or TypeScript with production code.
• Deep practical experience with retrieval-augmented generation and vector search.
• Experience building multi-step, tool-using agents and rigorous evaluation.
• Willingness to travel up to 15%.

Responsibilities

• Architect and ship agents across the portfolio, including knowledge and tool agents.
• Own the orchestration layer: planning, tool selection, state, retries, and termination.
• Design end-to-end retrieval: chunking, embeddings, indexing, and ranking.
• Build provenance and citations to explain conclusions and surface defects.
• Own the evaluation infrastructure for agent quality and cost.
• Integrate model providers and tools behind stable interfaces and monitor costs.
• Mentor engineers moving into AI from traditional software.
• Travel up to 15% for customer engagement and collaboration.

Skills

LLM-backed systems

Agentic systems

Python

TypeScript

Retrieval-augmented generation

Evaluation harnesses

Travel flexibility

Education

Bachelor's degree in Computer Science or related field

Tools

Vector search

Embeddings

Chunking strategies

Job description

Orbis 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

Own the agentic systems at the center of Orbis AI — the orchestration, planning, retrieval, and tool-use machinery behind the Agent Catalog and the OSINT Agent Harness. You will build agents that hold up under real mission workloads and set the evaluation bar the rest of the organization writes against. This is senior engineering on AI systems: the hard problems are correctness, explainability, cost, and behavior at scale.

Travel: Up to 15% for customer engagement, integration support, and team collaboration.

Key Responsibilities

• Architect and ship agents across the portfolio — knowledge agents over customer data, tool agents that wrap external operations, and goal-driven agents that plan and execute multi-step analysis.
• 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.

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.