Senior AI-DevOps Engineer
New
R
RelativityLegal Data Intelligence
Remote PolandFull-TimeSenior
Salary208 000 and 312 000PLN
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Job Details
- Languages
- English (C1)
- Experience
- 5+ years of experience in software, DevOps, or platform engineering, including at least 2+ years working on cloud platforms, infrastructure, or developer tooling
- Required Skills
- PythonArtificial IntelligenceKubernetesAzureFastAPICI/CDDevOpsGitHub Actions
Requirements
- 5+ years of experience in software, DevOps, or platform engineering.
- At least 2+ years working on cloud platforms, infrastructure, or developer tooling.
- Hands-on experience with Infrastructure-as-Code frameworks such as Pulumi, Terraform, Bicep, or CDK.
- Strong DevOps fundamentals including CI/CD pipeline design, GitHub Actions, container/Kubernetes basics, and observability.
- Experience building REST APIs in Python (FastAPI or Flask) with OpenAPI documentation and authentication.
- Knowledge of Azure fundamentals including Landing Zone patterns, identity, and secret management.
- Security-focused engineering mindset including least-privilege IAM, secret rotation, and auditability.
- Strong written English with experience working in async-first, distributed teams.
- Demonstrated senior-level ownership in system design, leading cross-team initiatives, mentoring, or building reusable platform patterns.
- C1 level English proficiency.
Responsibilities
- Design, build, and evolve reusable cloud provider patterns using Infrastructure-as-Code adopted across supplier teams.
- Contribute to the platform’s REST API contract layer using Python and FastAPI to ensure onboarding is reproducible and observable.
- Build and maintain CI/CD automation using GitHub Actions including reusable workflows and shared release patterns.
- Partner with consumer and supplier teams to run discovery sessions, document integration patterns, and unblock cross-team delivery.
- Track, measure, and communicate platform adoption metrics across teams.
- Use AI tooling in daily development workflows and contribute to internal AI-enabled engineering practices.
- Participate in a weekly on-call rotation, owning production incident response and systemic improvements.
- Produce comprehensive documentation including onboarding guides, runbooks, and architectural decision records.
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