11 дней назад
Software Engineer (AI Infrastructure)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer (AI Infrastructure): Building the cloud platform, deployment systems, and full-stack product features that power Hermes Agent, Hermes Cloud, and Nous Portal with an accent on scalable infrastructure, reliability, and production AI services. Focus on designing distributed systems, implementing CI/CD and observability, and optimizing inference infrastructure for performance, scalability, and cost efficiency.
Company
builds AI products and managed AI services including Hermes Agent, Hermes Cloud, and Nous Portal.
What you will do
- Design, build, and maintain the cloud platform powering managed AI services.
- Develop backend services, platform infrastructure, deployment systems, and user-facing applications end to end.
- Architect reliable and scalable infrastructure for inference, agent execution, and enterprise deployments.
- Build CI/CD pipelines, deployment workflows, and infrastructure-as-code systems.
- Implement observability, monitoring, alerting, incident response, and reliability improvements.
- Ship product features across Hermes Agent and Nous Portal while collaborating with Product, Research, and Engineering.
Requirements
- 3+ years of full-stack software engineering experience with substantial 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 AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, CI/CD, infrastructure-as-code, observability, monitoring, and production incident response.
- Ability to build across backend, infrastructure, and frontend systems and solve complex engineering problems.
- Interest in AI infrastructure and reliable systems for advanced AI applications.
Nice to have
- Experience operating high-throughput, latency-sensitive distributed systems.
- Familiarity with LLM infrastructure, inference systems, OpenAI-compatible APIs, model serving, or agent systems.
- Experience with serverless platforms, managed cloud infrastructure, or multi-cloud deployments.
- Open-source or AI ecosystem contributions.
- Experience improving production reliability, scalability, and cost efficiency.
Culture & Benefits
- Work closely with Research, Product, and Engineering on new AI capabilities and production launches.
- Balance delivery speed, reliability, and long-term maintainability when evaluating infrastructure and managed services.
- Operate in a fast-moving environment focused on building dependable AI systems.
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