Senior DevOps / Platform Engineer, AI Infrastructure

MAIA

. Take technical ownership of MAIA’s production infrastructure .

Posted 9/15/2026full-timeRemote • GermanySenior💰 €75,000 - €85,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing production infrastructure, particularly with Linux systems, Docker, and PostgreSQL, while ensuring security and compliance with ISO 27001. Capable of improving developer experience and operational resilience through effective incident response and observability practices.

Highest-signal resume keywords

Linux System AdministrationPostgreSQL ManagementInfrastructure as Code (Terraform, Pulumi)CI/CD Pipeline Development (GitHub Actions)Observability Stack Operation (Grafana, Prometheus)

ATS Keywords

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Hard Skills

Linux System AdministrationPostgreSQL ManagementDockerInfrastructure as Code (Terraform, Pulumi)CI/CD Pipeline DevelopmentObservability Stack OperationAPI Gateway ManagementIncident ResponseSecurity Practices (IAM, Secrets Management)Performance Analysis

Soft Skills

Fluent English CommunicationReliable Written CommunicationAccountabilityTechnical CuriosityCollaboration

Tools & Technologies

Docker ComposeGitHub ActionsGrafanaPrometheusLokiSentryTraefikKongVLLMHetzner

Certifications & Qualifications

ISO 27001 Compliance

Industry Keywords

SaaSInfrastructure SecurityObservabilityGenAIRAG Systems

Tech Stack

Tools & technologies

DockerGrafanaLinuxPostgresPrometheusTerraform

About the role

Key responsibilities & impact

Take technical ownership of MAIA’s production infrastructure
Operate and evolve self-administered Linux systems across virtual machines and dedicated servers
Manage containers, networks, reverse proxies, and API gateways
Improve Infrastructure as Code, GitHub Actions workflows, deployment processes, automated checks, versioning, and rollback capabilities
Make deployments safe, repeatable, and easy for engineers to use
Operate and improve PostgreSQL in production, including performance analysis, connection pooling, capacity planning, backups, and tested restore procedures
Develop the self-hosted observability stack connecting metrics, logs, traces, and actionable alerts
Strengthen infrastructure security through IAM, least privilege, secrets management, TLS, vulnerability scanning, and patch management
Implement technical controls for ISO 27001 with continuously generated, understandable, and auditable evidence
Shape AI infrastructure by integrating and evaluating model and inference providers
Evaluate providers based on reliability, latency, throughput, cost, and operational effort
Explore self-hosted LLM inference, potentially including GPU infrastructure and vLLM
Improve incident response and operational resilience through root-cause investigation, runbooks, documentation, and lasting improvements
Improve internal developer experience by reducing manual work and creating clear interfaces and workflows
Make infrastructure and inference costs transparent and inform build, buy, and hosting decisions
Assess the existing platform, identify risks, explain options, and take improvements through to reliable production operation
Collaborate with software engineers, the CTO, company leadership, and distributed team members
Work as a hands-on senior individual contributor without people management

Requirements

What you’ll need

Several years of experience operating production SaaS systems on Linux servers administered directly by you or your team
Experience limited to fully managed hyperscaler services is not sufficient
Production experience with Docker and Docker Compose
Understanding of reverse proxies or API gateways such as Traefik or Kong
Practical experience operating PostgreSQL, including personally configured and tested backups and restores, performance analysis, and connection pooling
Experience building and maintaining CI/CD pipelines using GitHub Actions, GitLab CI, or comparable systems
Experience managing infrastructure through Terraform, Pulumi, or comparable Infrastructure as Code tooling
Experience operating an observability stack using Grafana, Loki, Prometheus, Sentry, or comparable technologies
Understanding of IAM, least privilege, secrets management, vulnerability scanning, and patching
Ability to design infrastructure reliable for customers and straightforward for engineers to use
Fluent English communication
German helpful but not required
Understanding of how RAG systems work and where they commonly fail in production
Ability to discuss LLM serving trade-offs, including latency, throughput, reliability, cost, and operational complexity
Familiarity with models, inference providers, and the wider GenAI market
Strong platform engineering foundation and technical curiosity to develop deeper AI infrastructure expertise
Ability to independently operate business-critical production systems
Ability to identify and prioritise infrastructure work without detailed instructions
Ability to lead technical improvements across team boundaries
Reliable written and remote communication
Accountability after changes are deployed
Helpful but not required: experience with Hetzner, NixOS, self-hosted Supabase, ISO 27001 controls and audit evidence, SRE practices, GPUs, or LLM serving technologies such as vLLM

Benefits

Comp & perks

€75,000–€85,000 gross annual salary, depending on experience and scope
Opportunity to participate in our VSOP
Permanent, full-time position
Flexible working hours
Fully remote work from anywhere within Germany
Regular opportunities to meet and work with the team in Leipzig, with travel and accommodation covered
Access to a WellPass fitness membership