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• Take ownership of the operational delivery of the Azure Foundation within a broader cloud transformation program.
• Translate existing technical requirements and architecture designs into structured work packages, project plans, milestones and deliverables.

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Assistance in setting up and maintaining CI/CD pipelines
• Monitoring application and infrastructure performance
• Identification of application errors and configuration issues
• Collaboration with team members to streamline workflows and optimize system performance

• Fejlesztés és megvalósítás komplex generatív AI alkalmazásokban a felfedezéstől a bevezetésig
• Legjobb gyakorlatok keretrendszerének kialakítása felhőarchitektúrák telepítéséhez AI ügynökök támogatására, költség, teljesítmény és biztonság fókuszával LLM munkaterhelésekhez és vektor kereséshez

Design and maintain comprehensive solution architecture and technical design documentation, while delivering robust integration and backend solutions for enterprise applications and services...

• Architecture and delivery of production-grade LLM systems and classical ML solutions
• Design, evaluation, and optimization of RAG pipelines
• Building scalable, production-grade LLM services and agentic workflows alongside traditional ML systems

• Building one governed front door for every lead with validation, de-duplication, consent, and enrichment
• Building AI-native lead qualification models with comprehensive signal analysis and explainability
• Building intelligent lead routing with territory, capacity, availability, and priority data

• Éles AI infrastruktúra építése és karbantartása Infrastructure as Code (Terraform/CDK) használatával
• AI ügynökök gyors és biztonságos telepítésének támogatása monitoringgal, naplózással és telepítési automatizálással

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• End-to-end SRE ownership for the Global Fabric service
• Incident ownership across the customer journey from detection to resolution
• Primary operational escalation point for CF-related incidents
• Escalation of complex technical issues and coordination of resolution activities

• End-to-end felelősség cloud és on-premise platformok architektúrájáért
• Cloud platformok tervezése és fejlesztése (AWS, Azure, T Cloud Public)
• Kubernetes-alapú üzemeltetési és deployment megoldások kialakítása
• Shared és managed service architektúrák megtervezése és továbbfejlesztése

• Designing test strategies, test plans and test cases for complex, distributed systems
• Building and maintaining automated test suites (functional, integration, regression and end-to-end)
• Testing APIs and backend services, including validating data flows end to end

• Design and develop scalable cloud security automation solutions across multi-cloud environments
• Build and maintain platform services using modern engineering practices and a code-first approach
• Own and enhance CI/CD pipelines that enable secure, reliable and efficient delivery

Shaping and evolving the architecture of MDO network automation capabilities including reusable automation patterns, interfaces and technical guidelines...

Predictive ML: Build models for lead generation, demand forecasting, residual value forecasting, portfolio steering, and fraud detection....

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

CI/CD ownership: Own and evolve our shared GitHub Actions platform so it stays maintainable, reliable and easy to adopt across the team's repositories. Our stack is mainly Python, so you'll need a solid grasp of the Python packaging and tooling ecosystem. Occasionally you'll extend the platform to...

• Surgical microscopes creating surgical augmented reality
• Ultrasound devices creating 3D ultrasound imaging
• Brainlab's own Robotic Arm (Cirq)

• Design and implement cloud security controls across AWS, Azure, and GCP
• Build security automation using CI/CD pipelines, Infrastructure as Code, and Policy as Code
• Develop automated compliance checks and remediation workflows

• Planning, designing, implementing, and maintaining Rust components and applications
• Building a unified SDK for AI-based features integration into Aether
• Reviewing requirements and contributing to feature design
• Implementing clean, idiomatic, maintainable Rust code