AI Architect

Ameris Bank•Atlanta, GA

About The Position

The AI Architect owns the enterprise AI architecture, ensuring AI solutions are scalable, secure, interoperable, and aligned to business outcomes. They design end-to-end architectures and monitoring, establish standard patterns and build-vs-buy guidance, and partner with technology, data, security, and business teams to move AI initiatives from concept to production. Performs other projects and duties as assigned.

Requirements

Advanced proficiency with modern AI/ML and generative AI architectures.
Advanced proficiency in defining architectural standards, reference architectures, and reusable patterns, including AI patterns such as RAG, agentic workflows, and model orchestration.
Advanced proficiency in designing AI solutions involving data platforms, APIs, and enterprise integrations; strong ability to translate business problems into scalable AI solution designs.
Intermediate proficiency in supporting AI pilots, proofs of concept, and production deployments.
Intermediate proficiency in collaboration and communication with engineering, data, security, business stakeholders, and senior leadership.
Basic proficiency evaluating AI platforms, tools, models, and vendors objectively.
Basic proficiency with AI governance concepts including security, privacy, risk, and compliance.
Minimum 6 years of software engineering, data engineering, information security, or systems administration experience required.
Minimum 3 year of experience with AWS, GCP, Azure, or another cloud service preferred.
Bachelor's degree in computer science, information systems, or a related field required.

Nice To Haves

Previous financial services industry or FinTech experience strongly preferred.
Cloud platform certifications (e.g., AWS, Azure, or GCP) preferred.

Responsibilities

Defines and maintains the enterprise AI architecture and reference models.
Designs end‑to‑end AI solutions across data ingestion, models, orchestration, integration, and monitoring.
Selects, standardizes, and documents AI patterns (e.g., RAG, agentic workflows, ML pipelines, rules + AI hybrids).
Creates reusable AI assets, templates, and architectural guardrails to accelerate delivery.
Establishes build vs. buy vs. partner guidance for AI capabilities and platforms.
Evaluates, approves, and oversees AI tools, vendors, and platforms.
Ensures interoperability with core systems (core banking, CRM, ECM, data platforms).
Identifies opportunities to consolidate and standardize AI and automation solutions across the enterprise.
Leads and governs AI proofs of concept and pilots.
Supports AI business case development and guide solutions through implementation and production.