AI Architect – Internal Business Applications

MeridianLink

. Define and maintain the architectural vision, principles, standards, and governance framework for AI-first capabilities .

Posted 10/7/2026full-timeRemote • United StatesSeniorLead💰 $150,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable AI architectures, focusing on observability, reliability, and compliance. Proficient in developing enterprise data integration strategies and leading change management efforts for AI-enabled solutions.

Highest-signal resume keywords

AI/ML Systems DesignPython ProgrammingCloud Platforms (AWS, Azure, Google Cloud)MLOps and LLMOpsEnterprise Security and Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software ArchitectureData ArchitectureAPI DesignDistributed Systems ArchitectureIntelligent Automation SolutionsDocument ProcessingData ExtractionWorkflow AutomationLarge Language ModelsAgent Orchestration Frameworks

Soft Skills

Executive CommunicationStakeholder Management

Tools & Technologies

DockerKubernetesDatabricksSnowflake

Industry Keywords

AI-First CapabilitiesGovernance FrameworkNon-Functional RequirementsEnterprise Data IntegrationData Quality Standards

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerERPGoogle Cloud PlatformKubernetesPythonSQL

About the role

Key responsibilities & impact

Define and maintain the architectural vision, principles, standards, and governance framework for AI-first capabilities
Develop reference architectures for AI runtimes, model serving, security controls, identity management, policy enforcement, and secure enterprise data access
Establish non-functional requirements for reliability, performance, scalability, cost optimization, and compliance
Translate business and operational requirements from Finance, Human Resources, Operations, Customer Success, and other functions into scalable AI solution architectures and implementation strategies
Design and implement secure, compliant intelligent automation and decision-support solutions, including document processing, data extraction, workflow automation, and business process optimization
Establish enterprise data integration strategies, governance practices, and data quality standards across ERP, CRM, HCM, financial, and operational platforms
Develop APIs, reusable services, and foundational platform capabilities enabling scalable AI adoption
Partner with business and technology stakeholders to identify high-impact AI opportunities, evaluate feasibility, and define implementation roadmaps
Contribute to MLOps and LLMOps capabilities, including pipeline standardization, model observability, monitoring, lifecycle management, and production governance
Lead adoption and change management efforts supporting stakeholder alignment, trust, and effective utilization of AI-enabled solutions

Requirements

What you’ll need

8+ years of experience in software architecture, platform engineering, AI/ML systems design, data architecture, or related technical disciplines
4+ years of experience designing and deploying production-scale AI systems, including large language models, agent orchestration frameworks, and intelligent automation solutions
Deep expertise in modern AI architectures, including LLM serving, Retrieval-Augmented Generation (RAG), agentic orchestration, and AI workflow design
Demonstrated success designing and implementing enterprise-scale systems with a strong focus on observability, reliability, scalability, and cost optimization
Strong hands-on expertise with Python and SQL
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
Experience with Docker and Kubernetes
Experience with enterprise integrations, API design, and distributed systems architecture
Experience with MLOps and LLMOps tools, frameworks, and production best practices
Experience with modern data platforms such as Databricks and Snowflake
Strong executive communication and stakeholder management skills
Proven ability to provide architectural leadership from strategy and design through implementation and operationalization
Strong understanding of enterprise security, identity and access management, data governance, privacy requirements, and compliance frameworks
Background in computer science, engineering, or a related field is preferred
Ability to pass a background check, credit check, and drug test
Authorization to work in the United States is required

Benefits

Comp & perks

Insurance coverage (medical, dental, vision, life, and disability)
Flexible paid time off
Paid holidays
401(k) plan with company match
Remote work