AI Enablement Engineer Overview • The AI Enablement Engineer role focuses on developing and managing AI platforms, workflows, and governance for reliable and impactful adoption across the organization. • Collaborate with cross-functional teams to identify high-value AI use cases and translate them into actionable solutions. • Design and operate AI infrastructure with high reliability and security standards suitable for regulated environments. • Enable non-technical employees to utilize AI tools effectively through self-service workflows and training. • Develop reusable AI agent patterns and integration frameworks to streamline adoption across teams. • Ensure AI systems adhere to strict governance, auditability, and compliance requirements. • Remote work opportunity offering flexibility and collaboration with a dynamic team. • Contribute to architectural leadership and reference designs for scalable AI solutions. AI Enablement Engineer Key Responsibilities & Duties • Operate and evolve AI inference platforms, ensuring model reliability and cost efficiency. • Develop and maintain internal AI services and integration layers using modern programming languages. • Design and enforce identity-aware access controls and least-privilege IAM policies. • Build and manage AI usage analytics and reporting for operational visibility. • Author and curate high-quality prompts, skill definitions, and agent instructions with rigorous review processes. • Establish disciplined change management practices for AI infrastructure to ensure production stability. • Collaborate with business teams to train and coach on effective AI usage and development practices. • Monitor and optimize AI workloads to balance performance and cost efficiency. AI Enablement Engineer Job Requirements • Bachelor's degree in Computer Science, Engineering, or related field. • 5+ years of experience in software engineering, platform engineering, or DevOps. • Hands-on experience with large language models and AI platform engineering. • Proficiency in programming languages such as C#/.NET or Python. • Strong knowledge of AWS services, IAM policies, and infrastructure-as-code tools. • Experience defining SLOs, building observability, and designing reliable systems. • Exceptional communication skills for explaining AI concepts to diverse audiences. • Preferred experience in regulated environments such as fintech or payments.