Lead AI Architect

When you join Accurate Background, you’re an integral part of making every hire the start of a success story. Your contributions will help us fulfill our mission of advancing the background screening experience through visibility and insights, empowering our clients to make smarter, unbiased decisions.

Accurate Background is a fast-growing organization focused on providing employment background screening solutions and building trusted relationships with our clients. Accurate Background continues to exceed expectations by offering innovative background check and credentialing products.

The Lead AI Architect will play a key role in establishing and scaling Accurate Background’s emerging AI capabilities as part of a new team focused on building reusable AI platforms, AI engineering standards, experimentation practices, and production-ready AI solutions. This role will help define and operationalize an enterprise-grade AI Center of Excellence, including AI governance practices, AI lab experimentation, reusable agent and tool patterns, scalable AI solution architectures, and architecture standards for responsible AI adoption.

The Lead AI Architect will help transform the traditional Software Development Lifecycle into an AI Development Lifecycle — AI-DLC, materially changing how AI-enabled solutions are designed, evaluated, deployed, governed, monitored, and continuously improved. This role focuses on shaping AI architecture strategy and solution patterns that drive operational efficiency, improve user experiences, reduce risk, and generate measurable business and revenue value.

We offer a fun, fast-paced environment with significant opportunities for growth.

• Lead the architecture, design, and technical direction for AI-enabled solutions, including AI agents, tools, GenAI-powered applications, and reusable AI services
• Define enterprise AI architecture standards, reusable patterns, reference architectures, and engineering guardrails
• Establish foundational AI Center of Excellence standards to support scalable, secure, responsible, and production-ready AI adoption
• Architect and guide development of an AI lab for experimentation, prototyping, evaluation, model testing, and rapid iteration
• Define and operationalize AI-DLC practices, including experimentation, evaluation, governance, deployment, monitoring, and continuous improvement
• Design reusable and scalable AI platforms, services, APIs, orchestration patterns, and integration layers
• Partner with business and technology leaders to identify, prioritize, and deliver AI use cases that drive operational efficiency and measurable business value
• Define architecture patterns for GenAI capabilities such as RAG, prompt engineering, agent orchestration, tool calling, memory management, and human-in-the-loop workflows
• Architect AI agent ecosystems, tool integrations, and orchestration workflows across enterprise platforms and systems
• Provide technical direction on LLMs, SLMs, embeddings, vector search, model APIs, model selection, and AI service integration
• Create architecture blueprints, technical designs, reusable frameworks, decision records, and implementation standards
• Ensure AI solutions are secure, observable, maintainable, compliant, and aligned to enterprise architecture principles
• Establish and enforce AI governance practices, including responsible AI, data protection, privacy, compliance, auditability, and risk controls
• Guide deployment, monitoring, troubleshooting, and operational readiness of AI applications and platforms
• Define evaluation frameworks, quality benchmarks, feedback loops, and AI performance measurement approaches
• Partner with stakeholders to move AI ideas from concept through architecture, experimentation, production, and…