Senior AI/ML Engineer for Secure Geospatial LLMs

Vantor

Westminster (CO)

On-site

USD 145,000 - 205,000

Full time

6 days ago

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Benefits offered by this job

401(k) with company match

Mental health resources

Student loan repayment assistance

Adoption reimbursement

Pet insurance

Job summary

Vantor is seeking a Senior AI/ML Software Engineer to integrate secure chatbot and AI assistant capabilities into our geospatial intelligence suite. You will help analysts discover data, navigate applications, and complete approved workflows using natural language.

The role requires strong software engineering, practical LLM experience, and implementing safeguards against prompt injection and data leakage. Deployment in Kubernetes/OpenShift and SCIF environments is expected.

Qualifications

Bachelor’s degree or equivalent experience in CS/Software/AI.
8+ years of professional software engineering delivering production applications or services.
Hands-on experience integrating generative AI/LLMs into production software using patterns like RAG, embeddings, vector search, function calling, or agent workflows.
Strong Python skills and experience with JavaScript/TypeScript/Java/Go/C++ or other modern languages.
Experience building REST APIs or microservices and using Git, automated testing, CI/CD, and Agile practices.
Experience integrating enterprise data sources and applying secure identity/authorization/data-protection controls.
Willingness to work 75% in a SCIF environment in Herndon, VA; Denver, CO; or St. Louis, MO.
U.S. Person with TS/SCI with CI poly or ability to obtain clearance.

Responsibilities

Integrate AI chatbots/assistants into geospatial, analytics, visualization, and mission apps.
Build natural-language workflows for data discovery and navigation.
Implement LLM patterns like prompt orchestration, retrieval-augmented generation, and tool calling.
Connect AI services to REST APIs, data catalogs, search platforms, knowledge graphs, and dashboards.
Develop reusable backend services and frontend components for easy analyst use.
Enforce identity, entitlements, and data-access; provide citations, provenance, and audit records.
Test AI quality, safety, latency, and usability; protect against prompt injection and data leakage.
Deploy and operate AI services in Kubernetes/OpenShift, including restricted/disconnected environments.