Staff / Principal Platform Engineer
Inworld AI is a research lab and inference provider for realtime AI at consumer scale. It provides text-to-speech, speech-to-text, speech-to-speech, and LLM routing products for developers and businesses building consumer-facing applications.
Maintainer signals as of 9/25/2026
Funding history
Projects
About Inworld AI
Inworld AI develops and operates realtime AI infrastructure, including first-party text-to-speech and speech-to-text models, a customizable speech-to-speech Realtime API, and an LLM Router that routes requests across leading model providers. Its platform supports voice agents, social and companion applications, learning and education, health and wellness, agentic workforce applications, and games and media. The company serves developers, businesses, and teams building consumer-facing applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Own the end-to-end development, security, and scaling of Inworld's AI product infrastructure across major cloud providers. Partner with engineers to deploy services, improve engineering workflows, and shape operational practices.
Requirements
- 8-10 years of experience in software engineering.
- 3+ years of experience with infrastructure-as-code.
- Proficiency managing Kubernetes clusters and applications, including Kustomize manifests and Helm charts.
- Experience creating and maintaining CI/CD pipelines for application and infrastructure deployments using tools such as Terraform, Terragrunt, ArgoCD, GitHub Actions, and Ansible.
- Deep knowledge of at least one major cloud provider: Google Cloud Platform, Microsoft Azure, or Oracle Cloud.
- Proficiency in at least one backend programming or scripting language such as Golang, Python, or Bash.
- Must be based in the SF Bay Area or willing to relocate; the role requires working onsite in the South Bay office a few days per week.
Responsibilities
- Design, deploy, and maintain reliable, high-performance, and secure cloud infrastructure for TTS and LLM Router.
- Build AI-powered tooling and workflows that improve software development and deployment.
- Provide tools and processes for monitoring service reliability, availability, and performance.
- Manage code integration and deployment pipelines.
- Conduct root cause analysis and automate solutions to prevent recurring issues.
Benefits
- Equity