Gen AI Architect; Local to McLean, VA

Overview

Job Title: Gen AI Architect

Location: McLean, VA (100% Onsite – LOCAL CANDIDATES ONLY)

Interview Mode: Face-to-Face Interview Required

Duration: 12+ Months

Employment Type: Contract

Experience

Required:

8–10 Years

Important Note: Only local candidates who are available for in-person interviews should be submitted.

Job Summary: We are seeking an experienced Gen AI Architect to lead enterprise AI solution architecture initiatives, define AI transformation strategies, and establish enterprise-wide AI standards and governance frameworks. The ideal candidate will possess deep expertise in Generative AI, Large Language Models (LLMs), vector databases, cloud AI deployments, and Responsible AI practices. This role requires a strategic and hands-on AI leader capable of designing scalable AI architectures while collaborating with engineering, business, and executive stakeholders.

• 8+ years of experience in:
  • AI Architecture
  • Enterprise Solution Architecture
  • Machine Learning / Generative AI
  • Cloud AI Platforms
• Proven experience leading enterprise AI initiatives
• Experience designing scalable AI/GenAI solutions in enterprise environments

• Generative AI / LLM Expertise
  • Large Language Models (LLMs)
  • Generative AI frameworks
  • Prompt engineering concepts
  • AI orchestration frameworks
  • AI model lifecycle management
  • AI solution architecture
• AI Architecture
  • Enterprise AI architecture design
  • AI platform strategy
  • AI governance frameworks
  • Scalable AI deployment patterns
  • AI integration architecture
  • Multi-model AI ecosystems
• Vector Databases
  • Vector databases
  • Embedding architectures
  • Semantic search solutions
  • Retrieval-Augmented Generation (RAG)
  • Knowledge retrieval systems
• Cloud AI Deployments
  • AWS
  • Azure
  • Google Cloud Platform
  • Cloud-native AI deployment architectures
  • AI infrastructure scalability
  • Secure AI deployments
• Responsible AI / Governance
  • Responsible AI frameworks
  • AI governance
  • Ethical AI practices
  • AI risk management
  • Compliance and security considerations
  • Explainability and bias mitigation strategies

• Create and define enterprise AI solution architectures
• Establish AI standards, frameworks, and best practices across the organization
• Define long-term AI strategy and transformation roadmaps
• Design scalable GenAI and LLM-based enterprise solutions
• Lead architecture decisions for vector databases and retrieval systems
• Drive Responsible AI implementation strategies and governance
• Collaborate with engineering, business, and leadership teams
• Support cloud deployment and scaling of AI solutions
• Guide AI platform modernization and integration initiatives
• Evaluate emerging AI technologies, frameworks, and tools

• Experience implementing enterprise-scale GenAI platforms
• Experience with RAG architectures and AI copilots
• Exposure to AI Ops / MLOps frameworks
• Financial services or enterprise consulting experience preferred

• Master’s Degree in:
  • Computer Science
  • Artificial Intelligence
  • Machine Learning
  • Related technical discipline