Python programmer állás, munka

• Kapcsolattartás az ügyfelekkel, igények felmérése és tanácsadás
• Azure Function App fejlesztés
• Dokumentálás
• Programozás Pythonban
• Azure infrastruktúra tervezés és karbantartás
• Rendszeres ellenőrzés, frissítés és teljesítmény optimalizálás Azure környezetben
• Fejlesztések tervezésében aktív részvétel

• 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

• Management of end-to-end software release process including branch management
• Software version control
• Release note documentation
• Communication with internal and external collaborators
• Enhancement of CI/CD pipelines for release automation
• Defect logging and tracking for releases

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Work with an agile mindset and according to agile methodology
• Collaboration within the team, with other teams in the Domain and Deutsche Telekom, and with software engineers using the cloud platform
• Approach work with a DevOps and continuous improvement mindset

• 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

• Cooperation with software teams to establish and implement quality processes at every stage of the development cycle
• Development of automated test cases for firmware and Linux-based systems including bootloaders, kernel, device drivers and applications

• Design of reliable cloud architectures
• Partnership with customers, SRE teams, and internal stakeholders
• Championing automation
• Building reusable Infrastructure as Code templates and utility tools
• Design of secure cloud networks
• Driving customer success
• Operating platforms at scale

• Defining and communicating architectural vision for the Cloud Management Portal aligned with product strategy and customer outcomes
• Making pragmatic architectural decisions balancing modern practices with delivery speed and customer value

• Development and operation of Keycloak/RHSSO-based IAM capabilities on Kubernetes
• Standardization of deployment, configuration, and troubleshooting practices
• Continuous improvement of reliability, security, and automation around the IAM platform

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend

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

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Leading end-to-end penetration testing engagements across web applications, APIs, cloud environments, Kubernetes, AWS, Azure, GCP, and internal infrastructure
• Simulating real-world attack scenarios to identify security risks before they become threats