Role summary

We are looking for 2 strong DevOps engineers to build a repeatable deployment framework for enterprise AI and data applications. These engineers will take existing internally built apps and make them portable, secure, scalable, and deployable within client-owned environments. This is not just traditional infrastructure support — they will define the deployment architecture, production hardening standards, CI/CD model, observability patterns, and environment templates required to move AI/data-heavy applications from internal use into client production environments.

Responsibilities

- Design and implement a repeatable deployment framework for AI- and data-centric applications

- Build infrastructure-as-code, environment provisioning templates, and deployment automation

- Create CI/CD pipelines for dev, test, staging, and production releases

- Standardize application packaging so apps can be deployed into client environments with minimal rework

- Define patterns for secrets/configuration management, identity and access integration, networking and secure connectivity, observability/logging/monitoring/alerting, and rollback/release promotion

- Harden applications for production by improving resiliency, runtime controls, and operational readiness

- Partner with AI/fullstack engineers to ensure apps meet enterprise standards for performance, supportability, and maintainability

- Define a deployment model reusable across multiple apps rather than one-off approaches

- Produce runbooks, deployment guides, and operational documentation

- Support portability across client technology stacks and cloud environments

Required qualifications

- Strong experience in DevOps, platform engineering, or site reliability engineering

- Proven experience deploying enterprise web applications, data products, or AI-enabled applications

- Deep hands-on expertise with CI/CD pipelines, infrastructure as code, containerization/runtime packaging, secrets/configuration management, logging/monitoring/observability, and secure deployment practices

- Experience productionizing solutions that began as prototypes, analytics tools, or internal-facing apps

- Strong understanding of scalability, reliability, supportability, and security

- Experience moving applications from development into enterprise production alongside software engineers

- Strong communication skills and a collaborative, cross-functional build style

Preferred qualifications

- Experience with Azure-first environments

- Familiarity with analytics and AI deployment patterns (services, APIs, data platforms, model-enabled apps)

- Experience hardening enterprise applications for client deployment

- Familiarity with deployments across varying client environments and technology stacks

- Exposure to data-heavy and AI-heavy products where performance and portability are critical

What great looks like

A reusable deployment framework exists that supports current and future apps; internal apps deploy to client environments without being rebuilt; security, observability, release management, and production controls are standardized; and the team moves faster because deployment is no longer reinvented per use case.

Start date: ASAP

Duration: 3+ months with possible extension

HackerRank Challenge: No

Remote vs Onsite: Fully remote, with possible occasional in person team sessions / workshops / gatherings (i.e. 1x quarter) likely to take place in Prague

US Hours overlap needed: Minimum 2-6pm CET, preferred 2-7pm CET

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