The Role
As a Software Engineer on the Hermes Cloud team, you'll own full-stack engineering across the cloud platform that powers Hermes Agent and Nous Portal. You'll design and build the infrastructure, deployment systems, and platform services that keep our managed AI products reliable, scalable, and easy to operate.
This is a full-stack engineering role that spans infrastructure and product development. You'll help build the cloud platform while also shipping user-facing features, working closely with Product, Research, and Engineering to deliver exceptional AI experiences.
Responsibilities
Design, build, and maintain the cloud platform that powers Hermes Cloud and managed AI services.
Own software development end-to-end across backend services, platform infrastructure, deployment systems, and user-facing applications.
Architect scalable, reliable cloud infrastructure that supports inference, agent execution, and enterprise deployments.
Build and improve CI/CD pipelines, deployment workflows, and infrastructure-as-code to accelerate engineering velocity.
Implement observability, monitoring, alerting, incident response, and reliability improvements across production systems.
Optimize infrastructure performance, scalability, and cloud costs as product usage grows.
Ship full-stack product features across Hermes Agent and Nous Portal alongside platform improvements.
Evaluate and integrate third-party infrastructure and managed services where appropriate, balancing speed, reliability, and long-term maintainability.
Collaborate closely with Research, Product, and Engineering teams to support new AI capabilities and production launches.
Qualifications
3+ years of full-stack software engineering experience with significant ownership of cloud infrastructure or platform systems.
Strong programming skills in one or more of TypeScript/Node.js, Python, Go, or Rust.
Hands-on experience with modern cloud platforms such as AWS, Azure, or GCP.
Experience with containerization, orchestration, and deployment technologies including Docker and Kubernetes.
Familiarity with CI/CD systems, infrastructure-as-code, observability, monitoring, and production incident response.
Strong software engineering fundamentals with the ability to build across backend, infrastructure, and frontend systems.
Excellent problem-solving skills and the ability to operate effectively in a fast-moving environment.
Curiosity about AI infrastructure and enthusiasm for building reliable systems that support cutting-edge AI applications.
Nice-to-Have
Experience operating high-throughput, latency-sensitive distributed systems.
Familiarity with LLM infrastructure, inference systems, or OpenAI-compatible APIs.
Experience with serverless platforms, managed cloud infrastructure, or multi-cloud deployments.
Experience building or operating AI infrastructure, model serving platforms, or agent systems.
Contributions to open-source software or the AI ecosystem.
Experience optimizing production systems for reliability, scalability, and cost efficiency.