Python developer állások, munkák ai és automatizáció kategóriában

• Nemzetközi csapat tagjaként hosszú távú tesztelési feladatok különböző projektekben
• Új automatizálási keretrendszer fejlesztése low-code tesztautomatizáláshoz
• A keretrendszer karbantartása, gondozása és folyamatos továbbfejlesztése
• Innováció és új technológiák aktív bevonása és alkalmazása

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

• 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

• 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 implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Development and operation of the product in an engineering team
• Production deployments
• Cloud automation
• Monitoring and alerting
• Incident management and post-incident analysis
• Identification and troubleshooting of platform issues

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• 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

• Operational efficiency improvement through process optimization, automation, and adoption of new technologies
• Understanding the company's data warehouse and aligning data flows with reporting requirements
• Development and maintenance of reports and data-driven solutions using Power BI and Google Sheets

• Development of the test automation framework
• Development of test cases/steps
• Development of test tools
• Integration of testing tools into the automation framework

• 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

• Build and maintain scalable, reliable, and secure environment on AWS using Infrastructure as Code tools
• Oversee the deployment, configuration and management of clusters
• CI/CD pipeline development with designing and managing CI/CD pipelines, Infrastructure as Code, and GitOps toolset and skillset

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Experience in different data science topics including machine learning, LLM, deep learning
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• 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

• Development and fine-tuning of AI models including LLMs, Agentic AI, and Generative AI systems
• Building and deploying robust AI applications and services on cloud platforms
• Design and implementation of efficient AI pipelines from data preparation to model deployment and monitoring

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• Designing, developing, and evaluating machine learning models on complex telecom and retail data
• Transforming high-volume datasets into production-ready solutions such as churn prediction models and point-of-sale fraud models

• Integrációs megoldások tervezése és dokumentálása a legjobb gyakorlatok és vállalati irányelvek mentén
• Integrációs elvek és stratégiák formálása és fenntartása az Integration Architect csapattal együttműködve