Sr AI Architect - Internal Business Applications

The role

The Sr. AI Architect will define and lead the reference architecture for AI and intelligent automation across internal business operations. This role designs and implements complex AI systems to drive process optimization and autonomous workflows across various business functions.

What you will do

• Define and maintain architectural vision, principles, standards, and governance for AI-first capabilities.
• Develop reference architectures for AI runtimes, model serving, security, and data access.
• Establish non-functional requirements including reliability, performance, scalability, and compliance.
• Translate business requirements from various functions into scalable AI solution architectures.
• Design and implement secure intelligent automation and decision-support solutions.
• Establish enterprise data integration strategies and governance practices.
• Develop APIs, reusable services, and foundational platform capabilities.
• Partner with stakeholders to identify AI opportunities and define implementation roadmaps.
• Contribute to MLOps and LLMOps capabilities including pipeline standardization and monitoring.
• Lead adoption and change management efforts to support AI-enabled solutions.

Required qualifications

• 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 focus on observability, reliability, scalability, and cost optimization.
• Strong hands-on expertise with Python and SQL.
• Strong hands-on expertise with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Strong hands-on expertise with containerization and orchestration technologies, including Docker and Kubernetes.
• Strong hands-on expertise with enterprise integrations, API design, and distributed systems architecture.
• Strong hands-on expertise with MLOps and LLMOps tools, frameworks, and production best practices.
• Strong hands-on expertise with modern data platforms such as Databricks and Snowflake.
• Strong executive communication and stakeholder management skills.
• Strong understanding of enterprise security, identity and access management, data governance, privacy requirements, and compliance frameworks.

Nice to have

• Experience in fintech, financial services, or enterprise SaaS environments.
• Hands-on experience with LLM fine-tuning, prompt engineering, RAG systems, and vector databases.
• Prior experience enabling or architecting AI/ML workloads in enterprise environments.
• Familiarity with enterprise application ecosystems (ERP, CRM, HCM, financial systems) and integration patterns.
• Experience with event-driven architectures, real-time data processing, or workflow orchestration platforms.
• Understanding of AI governance, model monitoring, drift detection, and responsible AI frameworks.
• Background in computer science, engineering, or a related field.
• Prior experience in high-scale, product-based, or global environments.

About the company

MeridianLink is the employer for this role.