Senior AI Architect (Internal Business Applications)

MeridianLink, Inc.; United States; Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

MeridianLink, Inc. seeks an Sr. AI Architect to define and lead the reference architecture for AI and intelligent automation across its internal operations. The role focuses on scalable AI-enabled workflows, secure data access, and enterprise integration to accelerate business transformation.

You will design and implement AI solutions spanning Finance, HR, Operations, and Customer Success, combining deep technical leadership with hands-on execution to enable business enablement.

Qualifications

• 4+ years designing and deploying production-scale AI systems
• Strong knowledge of AI governance, model monitoring, drift detection, and responsible AI frameworks
• Hands-on expertise with Python and SQL; cloud platforms (AWS/Azure/GCP)
• Experience with MLOps/LLMOps, observability, and production governance
• Background in enterprise data integration and secure data access

Responsabilités

• Define and lead the reference architecture for AI and intelligent automation across MeridianLink's internal business operations
• Own end-to-end design and development of AI solutions and automation platforms
• Establish governance, security, and data quality standards for AI readiness across ERP/CRM/HCM systems
• Develop APIs and services to enable scalable AI adoption across business units
• Lead adoption, change management, and stakeholder alignment for AI-enabled solutions

Connaissances

AI architecture

Cloud platforms

Python

SQL

Leadership

Formation

CS/Engineering degree

Outils

Docker

Kubernetes

LLM tooling

Databricks

Snowflake

Description du poste

• The Sr. AI Architect, Internal Business Applications, will define and lead the reference architecture for AI and intelligent automation across MeridianLink's internal business operations, enabling secure, scalable AI-powered workflows and accelerating enterprise-wide business transformation. This role is responsible for designing, scoping, and implementing complex AI systems that operate at the intersection of business process optimization, AI workflow design, data architecture, enterprise integration, and organizational change
• The position owns the end-to-end design and development of modern AI solutions and intelligent automation platforms that drive process optimization, advanced analytics, decision intelligence, and autonomous workflows across Finance, Human Resources, Operations, Customer Success, and other business functions. Responsibilities include designing secure, reliable, and scalable solutions aligned with operational requirements, regulatory standards, and enterprise governance frameworks. The ideal candidate combines deep technical expertise with a hands-on approach to architecture, engineering leadership, and business enablement
• Define and maintain the architectural vision, principles, standards, and governance framework for AI-first capabilities, including intelligent automation, large language model (LLM) orchestration, agentic workflows, and enterprise integrations
• Develop reference architectures for AI runtimes, model serving, security controls, identity management, policy enforcement, and secure enterprise data access
• Establish non-functional requirements, including reliability, performance, scalability, cost optimization, and compliance standards, while defining service-level objectives and validation methodologies
• 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 that support AI readiness across ERP, CRM, HCM, financial, and operational platforms
• Develop APIs, reusable services, and foundational platform capabilities that enable scalable AI adoption across business teams and technology organizations
• Partner with business and technology stakeholders to identify high-impact AI opportunities, evaluate solution 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 to support stakeholder alignment, trust, and effective utilization of AI-enabled solutions and intelligent automation capabilities

Benefits

• Ongoing development: Continuous learning is essential to growth, and we're committed to helping our employees thrive. You'll have the opportunity to take part in job-specific training, monthly soft-skill sessions, and leadership classes designed to support your development at every stage.
• Access to executives: Have a good idea? Share it with peers, managers, or executives. Our leadership is approachable and actively involved in supporting your work.
• Health lifestyle: Healthy staff makes us happy. We support our team members with resources and programs that promote financial, physical, and mental health - encouraging balance, self-care, and a lifestyle that helps you feel your best every day.
• Celebrations: All work and no play makes for a dull day. We celebrate holidays, birthdays, work anniversaries, and other milestones with fun activities that bring us together. We also provide channels for employees to recognize and celebrate each other's achievements, making appreciation a regular part of our culture.
• Community partnering: Take a day off with pay to volunteer where it matters most to you or join the company in various community service projects throughout the year.

4+ years of experience designing and deploying production-scale AI systems, including large language models, agent orchestration frameworks, and intelligent automation solutionsUnderstanding of AI governance, model monitoring, drift detection, and responsible AI frameworksProven ability to provide architectural leadership from strategy and design through implementation and operationalizationPrior experience enabling or architecting AI/ML workloads in enterprise environmentsStrong understanding of enterprise security, identity and access management, data governance, privacy requirements, and compliance frameworksBackground in computer science, engineering, or a related fieldStrong executive communication and stakeholder management skills, with the ability to influence decisions and communicate complex technical concepts to both technical and non-technical audiencesStrong hands- on expertise with Python and SQL; cloud platforms such as AWS, Azure, or Google Cloud Platform; containerization and orchestration technologies, including Docker and Kubernetes; enterprise integrations, API design, and distributed systems architecture; MLOps and LLMOps tools, frameworks, and production best practices; and modern data platforms such as Databricks and SnowflakeHands- on experience with LLM fine- tuning, prompt engineering, RAG systems, and vector databases8+ years of experience in software architecture, platform engineering, AI/ML systems design, data architecture, or related technical disciplinesDemonstrated success designing and implementing enterprise-scale systems with a strong focus on observability, reliability, scalability, and cost optimizationPrior experience in high-scale, product-based, or global environmentsExperience in fintech, financial services, or enterprise SaaS environmentsFamiliarity with enterprise application ecosystems (ERP, CRM, HCM, financial systems) and integration patternsDeep expertise in modern AI architectures, including LLM serving, Retrieval-Augmented Generation (RAG), agentic orchestration, and AI workflow designExperience with event-driven architectures, real-time data processing, or workflow orchestration platforms