Platform & Systems Engineer – Power Systems

EnliteAI

. Shape the architecture of larger repositories, including module boundaries, interfaces, testing strategy and maintainability decisions .

Posted 9/21/2026full-timeVienna • AustriaMid-LevelSenior💰 €70,000 - €90,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining Kubernetes clusters, including deployment stack hardening and CI/CD processes. Proficient in Python and experienced in collaborating with cross-functional teams on complex infrastructure projects.

Highest-signal resume keywords

Kubernetes Operator-Level ExperienceSolid Python ExperienceHelm Chart AuthoringCI/CD DevelopmentInfrastructure Beneath Data Pipelines

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Engineering FundamentalsSystems InterfacesFailure ModesContainerized ServicesData Pipeline InfrastructureMQTTKafkaBackend ServicesAPIsGPU Scheduling

Soft Skills

Strong Communication SkillsSelf-DirectedCollaborative ApproachLow-Ego

Tools & Technologies

KubernetesHelmRedisCI/CD ToolsDeveloper Tooling

Certifications & Qualifications

Degree in Computer Science or Related FieldValid Work Permit for Austria

Industry Keywords

Stateful InfrastructureInfrastructure-as-CodeObservabilityPipeline OrchestrationTime Series at Scale

Tech Stack

Tools & technologies

KafkaKubernetesNode.jsPythonRayRedis

About the role

Key responsibilities & impact

Shape the architecture of larger repositories, including module boundaries, interfaces, testing strategy and maintainability decisions
Build and harden the deployment stack using containerised services on Kubernetes, Helm, Redis and related components
Own the demo and proof-of-concept path, enabling isolated instances with seeded data to be stood up within hours
Operate the Kubernetes cluster on company-owned hardware, including node lifecycle, GPU enablement, storage, networking, capacity planning and upgrades
Build infrastructure beneath data pipelines, including MQTT and Kafka brokers, topic and retention design, orchestration, storage, backend services and APIs
Build and harden CI/CD, developer tooling and the internal platform used by ML engineers and researchers
Collaborate with ML engineers, researchers and power systems experts on industrial and EU-funded projects

Requirements

What you’ll need

Fluent English with strong communication skills
Strong software engineering fundamentals, including systems, interfaces and failure modes
Solid Python experience in a substantial multi-person codebase
Kubernetes operator-level experience, including cluster upgrades, node replacement, and networking or storage debugging
Experience authoring Helm charts
Self-directed and able to work without a detailed roadmap
Low-ego and collaborative approach
A degree in computer science or a related field, or equivalent practical experience
Valid work permit for Austria
Desirable: production experience with stateful infrastructure such as Kafka, MQTT, Redis or databases
Desirable: infrastructure-as-code and observability experience
Desirable: pipeline orchestration, time series at scale, GPU scheduling on Kubernetes, or Ray experience
Desirable: lightweight proof-of-concept frontends or power-grid knowledge
German language skills are advantageous

Benefits

Comp & perks

Real ownership and a mandate to make architectural decisions
Ownership of the company's Kubernetes infrastructure on its own hardware
Cross-disciplinary team spanning reinforcement learning, optimization, data and platform engineering, and power systems
Work at the interface of academia and industry through EU Horizon projects
Work on critical infrastructure supporting the energy transition
Hybrid working: 2–3 days per week at the office in Vienna's 1st district, with minimal core hours
Dedicated time and budget for R&D, conferences and professional development