Senior AI/ML Software Engineer, Applied GenAI, RAG, and Intelligent Automation

Company: BPM Advisors, LLC

Location: Maryland (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-04-22

About this role

Work Type:
Remote-first, U.S.-based consulting role; required onsite onboarding in Annapolis, Maryland for the first 2 days, plus ability to report onsite within 72 hours when requested

Schedule:
Full-time business hours aligned to Eastern Time, with occasional after-hours support as needed

Duration:
Long-term public sector engagement, up to 5 years

Location Restriction:
Work must be performed within the United States

About the role

BPMA is seeking a highly capable
AI/ML Software Engineer
to support a secure public-sector technology program focused on practical, production-grade AI. This is not a research-only role. We need someone who can design, build, test, deploy, and continuously improve AI-enabled systems that automate narrowly defined tasks with high accuracy, improve internal productivity, and enhance user-facing services.

You will work across conversational AI, retrieval systems, intelligent automation, document workflows, and applied language technologies in a constrained, security-sensitive environment.

What you will do

  • Design and build production software that integrates AI/ML into real business workflows
  • Help define system architecture, agent workflows, data pipelines, and integration patterns
  • Determine when to use LLM-based approaches versus conventional algorithms or rules-based methods
  • Build and improve internal and external chatbots
  • Develop RAG, hybrid search, re-ranking, and knowledge retrieval capabilities
  • Support document-focused AI use cases including redaction, transcription, translation, document analysis, and document generation
  • Build and maintain testing and evaluation pipelines for AI-enabled systems
  • Create unit and integration tests for AI workflows and data pipelines
  • Use synthetic data and benchmarking techniques to evaluate quality, latency, and cost
  • Support containerized deployment in hybrid cloud environments
  • Optimize systems for constrained compute environments, including limited G...

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