Lead AI Architect

Accurate Background, Inc.; United States; Remote; USD 180,000 - 250,000; Full time

Job summary

Accurate Background, Inc. is seeking a Lead AI Architect to define and scale enterprise AI capabilities. You will shape governance, practice patterns, and production-ready AI solutions across AI labs and platforms.

You will lead architecture for AI agents, tools, and GenAI-powered applications, collaborating with business and technology leaders to deliver measurable value.

Qualifications

• Bachelor's degree in computer science or equivalent experience.
• 10+ years in software/architectural roles incl. cloud and AI architecture.
• 8+ years designing cloud-native solutions with modern patterns.
• Strong Python background and ability to guide Python-based AI services.
• Hands-on with AI-enabled apps, GenAI, agents, or AI platforms.
• Experience with AWS/Azure and AI-native PaaS services (Bedrock, OpenAI).
• Knowledge of GenAI patterns, agent frameworks, and orchestration tools.
• Familiarity with vector databases and retrieval systems.

Responsibilities

• Lead architecture and technical direction for AI-enabled solutions, agents and AI services.
• Define enterprise AI standards, patterns, reference architectures, and guardrails.
• Establish AI Center of Excellence standards for scalable, secure AI adoption.
• Guide AI lab development for prototyping, evaluation, and testing.
• Define AI-DLC practices: experimentation, governance, deployment, monitoring.
• Design scalable AI platforms, APIs, and integration layers.
• Partner with leaders to deliver AI use cases with measurable value.
• Define patterns for GenAI capabilities like RAG, prompts, and memory management.
• Architect AI agent ecosystems and orchestration across platforms.
• Provide direction on LLMs, embeddings, model APIs, and service integration.
• Create blueprints, designs, reusable frameworks, and implementation standards.
• Ensure AI solutions are secure, observable, and compliant with governance.
• Lead deployment readiness and performance measurement of AI apps.
• Mentor teams on AI-native architecture and responsible AI.
• Influence platform choice across AWS, Azure, and enterprise patterns.

Skills

Python

Cloud architecture

AI architecture

GenAI

AWS/Azure

LangGraph

Semantic Kernel

LLM ecosystems

Vector databases

Agent orchestration

Education

Bachelor's degree in computer science or equivalent experience

Tools

LangGraph

Semantic Kernel

Pinecone

Azure OpenAI

AWS Bedrock

Azure AI Foundry

Job description

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.

Job Description:

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.

Responsibilities:

• 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 scale
• Mentor engineers, architects, and product teams on AI-native architecture, AI engineering practices, and responsible AI solution design
• Influence technology selection and platform strategy across AWS, Azure, AI-native PaaS services, agent frameworks, observability tools, and enterprise integration patterns

Required Qualifications:

• Bachelor's degree in computer science or equivalent experience
• 10+ years of software engineering, solution architecture, enterprise architecture, cloud architecture, and/or AI architecture experience
• 8+ years of experience designing and delivering cloud-native solutions using modern architecture patterns
• Strong programming background, preferably with Python, and ability to guide architecture for Python-based AI services and applications
• Hands-on experience architecting or building AI-enabled applications, GenAI solutions, AI agents, or AI platforms
• Experience with AWS and/or Azure, including AI-native PaaS cloud services such as AWS Bedrock, AWS AgentCore, Azure AI Foundry, and Azure OpenAI
• Strong understanding of GenAI architecture patterns, including:
• Experience with agent frameworks and orchestration tools such as LangGraph, Semantic Kernel, or similar technologies
• Experience with LLM ecosystems and providers such as OpenAI, Anthropic, Llama, Mistral, or similar model providers
• Experience with vector databases and retrieval systems such as Pinecone, Azure AI Search, or equivalent technologies
• Experience with tool, agent,