Hi. We're Infinitus. We're a team of ex-Googlers, startup veterans, and industry experts on a mission to build AI that improves how Americans get access to critical specialty medications. Our purpose-built AI system automates phone calls to insurance companies, pharmacy benefit managers, and pharmacies to make the business of caring for people less "business," more "people."

Our approach combines multi-model/multimodal AI, human-in-the-loop machine learning, and an extensive knowledge graph to conduct accurate, compliant, autonomous conversations between organizations. Since Infinitus was founded over five years ago, we’ve automated over 3 million calls, processed more than 42 million minutes of audio, and saved the US healthcare system thousands of hours.

We’re backed by capital and industry leaders such as Kleiner Perkins, Coatue Management, and Gradient Ventures. If you're looking to join a dynamic team at the forefront of AI and health tech, and you’re ready to challenge "how it's always been done," we want to meet you.

As a Senior Engineer on our platform engineering team, you will take key ownership in developing cutting-edges end to end solutions using LLMs and other approaches and spearheading new projects. You'll be responsible for designing and delivering production systems that work with LLM AI Agents to handle complex phone call interactions. This position provides the opportunity to address significant technical challenges and drive the evolution of our AI infrastructure.

Responsibilities:

• Direct the development of APIs, ensuring they are robust, scalable, and adhere to high engineering standards.
• Design interfaces between our backend audio processing interfaces and our machine learning models.
• Define and drive improvements in key infrastructure components for conversational AI development, training, deployment, and scaling.
• Enable solutions from development to production, ensuring they are robust, scalable, and reliable and integrate well with our machine learning team.

Requirements:

• Proven experience in designing and implementing scalable, robust backend systems.
• Curiosity of machine learning concepts, algorithms, and infrastructure requirements.
• Expertise in languages such as Go, Python, Java, C++, or similar, with a focus on backend development. 
• Hands-on experience with cloud services like AWS, Google Cloud, or Azure, specifically for deploying ML models and backend services.
• Extensive experience in designing, developing, and maintaining APIs for seamless integration of backend services.
• Strong knowledge of database technologies, both SQL and NoSQL, and experience in optimizing database performance.