Ai Application Developer

Carnegie has led higher education marketing and enrollment strategy for over 30 years.Our groundbreaking services include research, strategy, digital marketing, lead generation, slate optimization, student search, website development, and creative that foster authentic connections.This role is responsible for building and maintaining AI applications on top of existing LLM APIs.We focus on integration, developing robust AI-driven applications, and optimizing their evaluation and performance.The ideal candidate will ensure that our AI applications are developed, configured, and adopted to meet evolving needs with a strong emphasis on Python-based solutions.Duties and ResponsibilitiesDesign, develop, and maintain scalable and secure AI applications using existing LLM APIs.Implement and manage integrations with various AI platforms and services.Develop and maintain Python-based applications, both cloud-deployed and on-premises, tailored for AI functionalities.Implement and manage CI/CD workflows for AI applications.Monitor and optimize AI application performance and cost, including model evaluation and optimization.Ensure data quality checks for AI models and applications escalate defects with clear reproduction steps and impact.Collaboration and CommunicationServe as a primary conduit among business leads, product managers, and AI engineering teams.Facilitate demos, knowledge-sharing sessions, and best-practice documentation for AI development.Promote adoption of new AI capabilities and practices, gathering feedback for continuous improvement.Release and Change ManagementCoordinate release plans, timelines, and stakeholder readiness for AI application deployments.Ensure training job aids and rollout communications are prepared and delivered for new AI features.Track post-release issues, adoption, and stabilization metrics for AI applications.Required Skills and QualificationsFamiliarity with existing LLM APIs and experience building applications on top of them.Experience with integrating AI applications into existing systems.Proficiency in Python and familiarity with AI-specific libraries and frameworks.Experience with optimizing AI model evaluation and performance.Cloud-based CI/CD workflows.Experience with Git and Git providers, such as GitHub, BitBucket, or GitLab.Nice-to-HavesCloud-based IAM networking and security.Experience with data orchestration frameworks, such as Airflow, Prefect, Dagster, or dbt.Experience with monitoring and observability tools for AI applications.Credentials and ExperienceCollege degree or equivalent life/work experience.At least 2 years in AI engineering, full-stack development with an AI focus, or related domains within SaaS, marketing technology, higher ed tech, or similar.At least 6 years in application development overall.