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AI Systems Architect (Full-Stack)

2 months ago
United States
Full-time
Lead
AI Engineer
Software Development
AWS Azure GCP LLM Machine Learning Microservices Reinforcement Learning
Apply Now
MPF Federal

MPF Federal

MPF Federal provides a comprehensive array of business services, including interactive multimedia training and logistics support, aimed at helping both federal government and commercial clients develop a skilled workforce and achieve their organization...

Professional Services
51-250
Founded 2012
View All Jobs 2

Description

  • Lead the design and development of AI-driven tools for deployment across AWS, Azure, and Google Cloud.
  • Design and deploy applications for internal and external use.
  • Build products that enforce operational discipline and governance across multi-cloud environments.
  • Develop end-to-end full-stack applications with real-time decision support interfaces and high-concurrency backend engines.
  • Design asynchronous APIs for live, multi-modal data ingestion from diverse sources.
  • Architect systems that collect, analyze, and orchestrate stateful variables in real time to drive predictive outcomes.
  • Collaborate across business departments to align technical solutions with organizational needs.
  • Ensure application performance and portability across a multi-cloud landscape.
  • Own architectural decisions and end-to-end development from data ingestion through model integration and visualization.

Requirements

  • 10+ years of full-stack development experience, with at least 4 years focused on AI/ML integration.
  • Proven success building and deploying applications in secure, multi-tenant cloud environments.
  • Experience designing unified data stacks that synchronize real-world human interactions with virtual system states in real time.
  • Experience developing autonomous AI agents using frameworks such as LangGraph, AutoGen, or CrewAI.
  • Experience building pipelines for text, telemetry, and unstructured audio data to drive real-time system updates.
  • Proficiency in agent-based modeling and reinforcement learning for complex decision-making cycles.
  • Deep experience with LLMs and vector databases for dynamic content generation and contextual memory.
  • Demonstrated ability to work independently, manage technical debt, and make architectural trade-offs.
  • Experience navigating technical and security constraints in government or heavily regulated industries.
  • U.S. citizenship required.

Benefits

  • Competitive compensation package with a salary of $150k–$180k, depending on verified experience.
  • Medical benefits.
  • PTO.
  • Holiday pay.
  • Opportunity to build greenfield systems and MVPs rather than maintain legacy tools.
  • High-trust, low-bureaucracy environment with strong engineering ownership.
  • Equal opportunity employment consideration.

Interested in this position?

Apply directly on the company website

Apply Now

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