AI Architect - Internal Business Applications
$150k - $200k • US Remote • FullTime
Posted 10d ago
About the job
MeridianLink is seeking an AI Architect to define and lead the reference architecture for AI and intelligent automation across its internal business operations. This role will enable secure, scalable AI-powered workflows and accelerate enterprise-wide business transformation by designing, scoping, and implementing complex AI systems. The architect will own 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 various business functions. Responsibilities include designing secure, reliable, and scalable solutions aligned with operational requirements, regulatory standards, and enterprise governance frameworks, combining deep technical expertise with a hands-on approach to architecture, engineering leadership, and business enablement.
Responsibilities
- Define and maintain the architectural vision, principles, standards, and governance framework for AI-first capabilities, including intelligent automation, 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 (reliability, performance, scalability, cost optimization, compliance) and define service-level objectives and validation methodologies.
- Translate business and operational requirements 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 for AI readiness across platforms.
- Develop APIs, reusable services, and foundational platform capabilities for scalable AI adoption.
- Partner with 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 to support stakeholder alignment, trust, and effective utilization of AI-enabled solutions.
Requirements
- 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.
- Proficiency with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with containerization and orchestration technologies, including 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 through operationalization.
- Strong understanding of enterprise security, identity and access management, data governance, privacy requirements, and compliance frameworks.