Senior Software Engineer, Agentic AI

2 hours, 48 minutes ago
Full-time
Senior
Software Development
Orbis

Orbis

Orbis specializes in providing comprehensive analysis and insights into the digital domain through its Digital Landscape Discovery service, which systematically collects, processes, and interprets digital information to support national security initia...

Professional Services
11-50
Founded 2008

Description

  • Architect and ship knowledge, tool-using, and goal-driven agents across the AI portfolio.
  • Own agent orchestration, including planning, tool selection, state and memory, retries, partial failures, and termination behavior.
  • Design and manage end-to-end retrieval systems, including chunking, embeddings, indexing, ranking, and query-time behavior.
  • Build provenance and citation paths so users can understand how agent conclusions were reached.
  • Own evaluation infrastructure for agent accuracy, groundedness, explainability, latency, and cost.
  • Integrate model providers and third-party tools through stable internal interfaces.
  • Instrument agents to identify quality regressions and cost anomalies before they affect customers.
  • Partner with research engineers to productionize validated results and mentor engineers transitioning into AI work.
  • Travel up to 15% for customer engagement, integration support, and team collaboration.

Requirements

  • 4+ years of professional software engineering experience, including 2+ years building production LLM-backed or agentic systems.
  • Bachelor's degree in Computer Science or a related technical field, or equivalent professional experience.
  • Strong Python and/or TypeScript programming skills, with substantial production experience in at least one.
  • Deep practical experience with retrieval-augmented generation, including embeddings, vector search, chunking, ranking, and failure modes.
  • Experience building and debugging multi-step, tool-using agents using frameworks or primitives.
  • Demonstrated rigor in AI evaluation, including building harnesses to measure the impact of changes.
  • Willingness to travel up to 15%.
  • Experience with knowledge graphs, ontologies, entity resolution, or information extraction (preferred).
  • Experience running open-weight models in constrained or disconnected environments (preferred).
  • Familiarity with production observability, model-workload cost control, OSINT or intelligence workflows, mentoring engineers into AI work, or applied-AI open-source, publication, or academic contributions (preferred).

Benefits

  • Competitive retirement matching.
  • PTO policy designed to encourage meaningful time off.
  • Comprehensive benefits package for employees and their families, with full details shared during the hiring process.
  • Work arrangement based on mission needs, which may include customer-site, office-based, hybrid, or fully remote work.
  • Tools and access needed to work effectively across supported locations.

Interested in this position?

Apply directly on the company website

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