Senior Applied AI Solutions Architect, Federal Financial

Amazon Amazon · Big Tech · Arlington, VA · Solutions Architect

Senior Applied AI Solutions Architect for Federal Financial Regulatory customers, focusing on designing and enabling AI/ML solutions for fraud detection, market surveillance, regulatory reporting, and consumer protection. The role involves technical guidance, developing reference architectures, and enabling customer adoption of AI/ML on AWS, with a strong emphasis on agentic systems and RAG.

What you'd actually do

  1. Be the Subject Matter Expert (SME) for designing applied AI solutions that help federal financial regulatory agencies automate workflows, accelerate decision-making, and drive down costs.
  2. Work closely with other Specialist and Generalist Solutions Architects to enable large-scale customer use cases and drive adoption of AI/ML across the federal financial portfolio.
  3. Interact with customers and SAs in the field, providing technical guidance on AI/ML engagements, and you will develop white papers, reference architectures, and presentations to enable customers and partners to fully leverage applied AI on AWS.
  4. Create field enablement materials for the broader SA population, helping them integrate AI solutions into customer architectures.

Skills

Required

  • Designing applied AI solutions
  • AI/ML
  • Generative AI
  • Agentic systems
  • Retrieval-augmented generation (RAG)
  • Intelligent document processing
  • Conversational AI
  • Classification/anomaly detection
  • Python
  • AWS

Nice to have

  • Statistics
  • Mathematics
  • Computer Science
  • Enterprise-grade AI/ML solutions architecture
  • AWS experience

What the JD emphasized

  • must have the ability to obtain and maintain a security clearance
  • U.S. Citizen
  • deep technical experience working with technologies related to artificial intelligence, machine learning, deep learning, or generative AI
  • must be comfortable operating in Python data science environments
  • must have outstanding communication skills

Other signals

  • designing applied AI solutions
  • customer use cases
  • technical guidance on AI/ML engagements
  • develop white papers, reference architectures, and presentations
  • field enablement materials
  • deep technical experience working with technologies related to artificial intelligence, machine learning, deep learning, or generative AI
  • architect enterprise-grade AI/ML solutions
  • modern AI patterns and architectures — including agentic systems, retrieval-augmented generation, intelligent document processing, conversational AI, and classification/anomaly detection
  • operating in Python data science environments
  • build production-ready solutions