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AI​/ML Engineer

Job in McLean, Fairfax County, Virginia, USA
Listing for: Vantor
Full Time position
Listed on 2026-07-07
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Python, Full Stack Developer
Job Description & How to Apply Below

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can:
Shape your own future, build the next big thing, and change the world.

To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.

Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Please review the job details below.

This position requires an active U.S. Government Security Clearance at the TS/SCI level with required polygraph.

Responsibilities:

  • Develop, implement, and maintain AI/ML-enabled applications with a focus on agent-based workflows, LLM integration, and retrieval-augmented generation capabilities.
  • Design and support agent-based application architectures, including orchestration logic, tool use, memory management, and integration with external systems.
  • Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, prompt assembly, and response optimization.
  • Integrate LLMs into applications using available APIs, AI frameworks, and emerging protocols such as MCP.
  • Develop and maintain REST APIs, particularly Python-based services, to support data retrieval, system integration, agent workflows, and application functionality.
  • Support full-stack development of production-ready AI applications, including backend services, user-facing components, and enterprise deployment considerations.
  • Process, transform, and organize structured and unstructured data to support AI/ML workflows, model interaction, and application performance.
  • Design or refine Postgres schemas and data models to improve data organization, query performance, and application scalability.
  • Optimize AI-enabled applications for performance, reliability, usability, and maintainability in enterprise environments.

Minimum Qualifications:

  • Bachelor’s degree in computer science or related area of study.
  • Senior Labor Category:
    Minimum 8 years of experience with a Bachelor’s degree; or 7 years of experience with a Master’s degree; or 6 years of experience with a Doctorate.
  • Active/current TS/SCI with required polygraph.
  • Willingness to work onsite full time.
  • US citizenship required.
  • Proficiency in Python and common data/AI libraries.
  • Experience developing AI/ML applications, including LLM-integrated applications, RAG workflows, or similar retrieval-based capabilities.
  • Experience with agent-based programming concepts, AI frameworks, and tool-based LLM application development.
  • Strong understanding of AI/ML foundational concepts, including transformers, algorithms, LLM behavior, data processing, and model integration patterns.
  • Experience designing, developing, or integrating REST APIs to retrieve, process, or exchange data across systems.
  • Familiarity with production-ready application development practices, including reliability, maintainability, testing, and deployment considerations.

Preferred Qualifications:

  • Experience with MCP or similar protocols for connecting AI agents to tools, data sources, and enterprise systems.
  • Experience developing full-stack agent-based applications, including frontend interfaces, backend services, orchestration layers, and enterprise deployment patterns.
  • Experience with Python REST API frameworks such as FastAPI or Flask.
  • Experience implementing or optimizing LLM memory management approaches, including conversational memory, session state, context management, and retrieval-based memory.
  • Experience with agent-based application optimization techniques, including prompt/tool orchestration, latency reduction, context window management, evaluation, observability, and cost/performance tuning.
  • Experience working with vector databases, embedding models, semantic search, and retrieval configuration.
  • Experience with Docker containers and…
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