AI Software Engineer (TS/SCI)

Vantor•Herndon, VA

About The Position

Vantor is seeking a Senior AI/ML Software Engineer to integrate secure chatbot and AI assistant capabilities into existing geospatial intelligence, analytics, visualization, and mission-support tools. The role helps analysts discover data, navigate applications, and complete approved workflows using natural language. It calls for strong software engineering skills, practical experience with LLMs, and an understanding of secure, usable AI in mission environments. The position requires U.S. citizenship and an active U.S. Government TS/SCI security clearance; employment is contingent on verification of clearance status. The candidate must be willing to obtain a CI poly. Certain roles may also be subject to U.S. export control laws requiring U.S. person status. The position is based on a salary range of $140,000–$200,000. Starting pay depends on job-related factors, including experience, qualifications, skills, geographic work location, and market conditions.

Requirements

U.S. citizenship and an active TS/SCI clearance; willingness to obtain a CI poly.
Bachelor's degree in computer science, software engineering, data science, artificial intelligence, or a related field.
At least 8 years of professional software engineering experience delivering production applications or services.
Hands-on experience integrating generative AI or LLMs into production software applications using patterns such as RAG, embeddings, vector search, function calling, or agent workflows.
Strong Python skills and experience with JavaScript, TypeScript, Java, Go, C++, or another modern language.
Experience building REST APIs or microservices and using Git, automated testing, CI/CD, and Agile development practices.
Experience integrating enterprise data sources and applying secure identity, authorization, and data-protection controls.

Nice To Haves

Experience building chatbot interfaces with React, TypeScript, or comparable web frameworks and applying usability practices.
Experience with AI orchestration frameworks, model gateways, MCP-compatible services, or agent-to-tool integration.
Experience deploying commercial, open-source, or locally hosted LLMs in cloud, on-premises, classified, air-gapped, or disconnected environments.
Experience with vector search, Elasticsearch, knowledge graphs, GIS, imagery, geospatial applications, or other mission-critical systems.
Experience with AI safety controls, human-in-the-loop approvals, model monitoring, evaluation, GPU workloads, or model serving.
Experience with containers and Kubernetes; Red Hat OpenShift experience is preferred.

Responsibilities

Integrate AI chatbots and assistants into existing geospatial, analytics, visualization, and mission applications.
Build natural-language workflows for data discovery, application navigation, visualization generation, and approved actions.
Implement LLM patterns such as prompt orchestration, retrieval-augmented generation, tool calling, and conversation context.
Connect AI services to REST APIs, data catalogs, search platforms, knowledge graphs, geospatial services, notebooks, and dashboards.
Develop reusable backend services and frontend components that make AI assistance simple for analysts to use.
Enforce identity, entitlements, and data-access policies; provide citations, provenance, audit records, and clear system limitations.
Test and evaluate AI quality, safety, latency, and usability, including protections against prompt injection, data leakage, and unauthorized actions.
Deploy and operate AI services in Kubernetes and Red Hat OpenShift, including restricted or disconnected environments.
Collaborate with technical and customer teams.