AI Engineer

The Opportunity  

What You’ll Be Doing  

What You'll Be Doing

Required

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.
• 5–7 years of experience in software engineering, machine learning engineering, platform engineering, or a related area building and operating production systems.
• Strong proficiency in at least one modern programming language such as Python, Go, or TypeScript, along with solid software design, debugging, and engineering fundamentals.
• Experience building and operating services on a major cloud platform, preferably Google Cloud Platform, including familiarity with compute, storage, networking, and managed services.
• Hands-on experience with containers and orchestration technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and Git-based engineering workflows used to build, test, and deploy services and platform components.
• Familiarity with infrastructure-as-code tools such as Terraform for provisioning and managing cloud resources in a repeatable, auditable way.
• Familiarity with MLOps concepts and tools used to support model training, evaluation, deployment, and monitoring.
• Understanding of modern AI capabilities such as generative AI, embeddings, retrieval patterns, NLP, and related ML concepts, and the ability to apply them responsibly in production environments.
• Experience building APIs, services, platforms, or libraries that are consumed by other engineers, with a focus on reliability, usability, and documentation.
• Strong foundation in observability and operational excellence, including experience managing service health through metrics, logs, dashboards, and alerting.
• Experience working cross-functionally with product, data, infrastructure, platform, and security teams.
• Ability to translate technical topics into practical guidance and collaborate effectively in a distributed, remote-friendly environment.

Preferred

• Experience supporting shared AI enablement, developer productivity, or platform engineering initiatives in a multi-team SaaS environment.
• Experience with Google Cloud AI and data services such as Vertex AI, BigQuery, or related managed tooling.
• Familiarity with AI evaluation frameworks, guardrails, prompt management, model routing, and lifecycle governance.
• Experience working with vector search, retrieval-augmented generation, agentic workflows, or orchestration frameworks in production settings.
• Exposure to intelligent search, recommendation systems, NLP, or computer vision use cases.
• Background working in environments where security, governance, and operational reliability are important to AI adoption.

Physical Demands and Work Environment: 

• The physical activities of this position include frequent sitting, telephone communication, and working on a computer for extended periods. Visual acuity is required to perform activities close to the eyes. 

• Team members are expected to maintain a dedicated and ergonomically appropriate remote workspace. 

• Team members who live within commuting distance of one of our office locations (Greater Cincinnati/Northern Kentucky or Atlanta, Georgia) are expected to work in a hybrid capacity, with regular in-office presence as determined by the team or department. 

• All team members must reside and perform their work within the United States.