AI Engineer, Principal

• Development: Collaborate with data scientists and ML engineers to containerize, deploy, and monitor AI/ML models.
• Infrastructure-as-code: Design, build, manage cloud infrastructure using Terraform to support scalable, secure, and cost-efficient AI workloads.
• Manage AI Services: Deploy and manage AI services preferably on AWS (e.g., SQS, Lamda, ECS/EKS, S3, IAM, CloudWatch).
• Backend Integration: Connect AI Services to backend systems and services via RESTful APIs, leveraging authentication, session management, and error handling best practices.
• Platform Engineering: Architect and implement multi-channel support (chat, voice) to ensure consistent experiences across platforms.
• Code Quality & Testing: Write clean, efficient, testable code. Develop unit and integration tests and participate in code reviews.
• Performance Monitoring: Use analytics tools to track AI Services performance, identify issues, and recommend improvements.
• Cross-Functional Collaboration: Work closely with Platform engineers, QA testers, and product managers to align development with business goals.

• 3+ years in Software Development, including 1 year specifically focused on Data Science, Machine Learning Capabilities, or Cloud Infrastructure roles.
• Proficient in Python; additional experience with Terraform, JSON, and XML is a plus.
• Familiarity with Containerization (Docker) and Orchestration (Kubernetes or ECS)
• Familiarity with CI/CD Pipelines, version control systems (e.g., Git), and Agile Development practices.
• Experience integrating with third-party APIs and enterprise systems.
• Understanding MLOps principles and Model Lifecycle Management.
• Strong problem-solving skills and ability to work in an agile, collaborative environment.

• DevOps experience: familiarity with CI/CD pipelines, infrastructure monitoring, logging tools (e.g. Prometheus, Grafana, ELK), and configuration management.
• Exposure to infrastructure security, networking, or compliance in cloud environment.
• Experience building or integrating AI models into real-time voice or telephony systems (e.g. voice bots, call centers or IVR).

• Fully remote work with flexible hours.
• Support for certifications, ongoing education, and career advancement.
• A mission-driven team committed to improving healthcare access and equity.

NOTE: Video cameras must be used during all interviews, as well as during the initial week of orientation