Senior DevOps / Platform Engineer, Voice AI

Shelf is a company focused on enabling GenAI deployment at scale with core infrastructure. Founded in 2017, it has raised over $60 million in funding from investors including Tiger Global and Insight Partners. The company has over 100 employees across the U.S. and Europe and is experiencing high growth with 3X growth for three consecutive years.

• Strong senior-level experience in platform engineering, DevOps, SRE, infrastructure engineering, or a similar hands-on role.
• Strong cloud and infrastructure fundamentals in AWS, Azure, or a comparable environment.
• Real experience with infrastructure as code and modern delivery pipelines.
• Strong operational judgment around reliability, observability, incident response, and production systems.
• Comfort moving across layers: infrastructure, backend services, developer workflows, and operational tooling.
• Clear communication and strong written habits, especially around runbooks, postmortems, and technical decision making.
• AI-native working style, using AI tools in daily engineering work.

Strong Plus:

• Hands-on experience deploying or operating STT, TTS, STS, or similar voice-model workloads.
• Experience improving developer experience for product teams.
• Experience with security, access control, compliance-minded infrastructure, and operational guardrails.
• Ability to debug problems across application code, infrastructure, and third-party systems.

• Improve how Voice AI services are deployed, run, observed, and supported in production.
• Build and maintain infrastructure as code, CI/CD flows, environment setup, and paved paths that reduce developer friction.
• Strengthen observability with better logs, metrics, traces, dashboards, and alerts.
• Improve reliability through better operational standards, incident handling, post-incident follow-through, and practical SLO thinking.
• Work across application and infrastructure boundaries when required.
• Reduce recurring toil through automation, documentation, and better defaults.
• Make sound trade-offs around cost, security, performance, and speed.
• Use AI tools aggressively to increase leverage and improve engineering workflows.

Work location is Warsaw, Poland, with work from the office (hybrid).