Senior DevOps / Platform Engineer, Voice AI

About Shelf

Shelf builds software that helps enterprises make AI work in the real world. For our Voice AI product, that means reliable runtime systems, strong deployment paths, and production infrastructure that lets engineering teams move fast without creating operational chaos.

About the role

This role is for a senior DevOps / platform engineer who can independently own how our Voice AI product ships and runs.

You will work directly with the team building our Voice AI product rather than as part of a generic centralized Platform function. The job is to make deployment, reliability, observability, and operational quality materially better. That includes infrastructure, CI/CD, environments, incident follow-through, and the practical realities of running AI-heavy systems in production.

Real hands-on experience deploying voice-related systems such as STT, TTS, or STS workloads is a strong plus because it is highly relevant to the direction of the work.

Location – Poland remote, with travel for onboarding and periodic in-person collaboration.

What You Will Own

• 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 that is what the problem requires.

• Reduce recurring toil through automation, documentation, and better defaults.

• Make sound trade-offs around cost, security, performance, and speed.

• Use AI tools aggressively and well to increase your own leverage and improve engineering workflows.

What Strong Performance Looks Like

• The Voice AI team can ship faster and with fewer avoidable operational issues because of your work.

• The systems you touch become easier to understand, easier to operate, and easier to trust.

• You do not need heavy management to create momentum; you find important gaps and close them.

• You handle real production problems without drama and improve the system after the immediate issue is over.

What We Are Looking For

• 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. You already use AI tools in daily engineering work and think in terms of leverage, automation, and better workflows.

Strong Plus

• Real hands-on experience deploying or operating STT, TTS, STS, or similar voice-model workloads.

• Experience improving developer experience for product teams, not just operating infrastructure in isolation.

• Experience with security, access control, compliance-minded infrastructure, and pragmatic operational guardrails.

• Ability to debug problems that cut across application code, infrastructure, and third-party systems.

How We Evaluate Fit

We care more about independent ownership, systems judgment, and practical operating ability than about a perfect keyword match to every tool we use. If you are the kind of engineer who can step into a messy production environment and make it calmer, faster, and more reliable, we want to talk.

What Shelf Offers

• B2B contract

• Company Stock Options

• Hardware: MacBook Pro

• Modern technical stack. Develop open-source software

• Premier AI development environment: GitHub Copilot, Claude Code, OpenAI, TypingMind, v0, MCP Servers, plus credits to experiment with emerging AI tools

Why Shelf:

• GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scale

• Our Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this plan

• We've been helping our customers prevent knowledge mismanagement since our founding in 2017

• We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and others

• We have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a row

• We now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few months