Python developer állások XI. kerületben (ai és automatizáció)

• Industrialize AI-assisted engineering workflows for Meridian
• Package repeatable patterns supporting codebase intake, dependency extraction, build triage, documentation generation, and technical evidence creation across cloud software work packages

• Strengthening Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Komplex AI megoldások fejlesztése ügyfelek számára (chatbotok, service botok, LLM-alapú alkalmazások)
• RAG (Retrieval-Augmented Generation) alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal

• Monitoring platform and resolving issues reported by monitoring application
• Maintaining availability, integrity and confidentiality of security platforms
• Upgrading, remediating and patching underlying operating systems including Windows, Linux, ESXi, firewalls

• Analysis and research of cloud-native tools and frameworks for Google Cloud Platform solutions
• Support for the T-Systems Public Cloud Product Management Team in building and defining solutions

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifacts
• Conducting regular 1-on-1s for career development and feedback
• Driving task prioritization, sprint planning, and resource allocation

• Architect Zero-Trust environments for LLM-based solutions
• Implement private networking (Private Link), granular RBAC (Entra ID), and automated policy enforcement
• Ensure compliance with enterprise security and audit standards
• Bridge Data Science and Engineering

Work directly with clients, product owners, architects, and development teams to understand business and technical requirements and translate them into infrastructure and cloud architecture requirements...

• Planning, implementation, development and testing of HW/SW components for the company backbone and data center networks
• Preparation of technical feasibility studies, design proposals and execution of POCs for the networks

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, dataset documentation

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines including IaC scanning and policy-as-code

• Skálázható cloud-native adatarchitektúrák tervezése Databricks vagy MS Fabric platformokra
• Adatmodellek, sémák és tárolási minták kialakítása (lakehouse, Delta, Parquet)
• Batch és streaming adatok betöltési pipeline-jainak megtervezése
• ETL/ELT folyamatok és transzformációs stratégia meghatározása

Agent workflows with LangGraph / LangChain / PydanticAI / CrewAI (routing, retries, fallbacks, timeouts, human-in-the-loop)....

• Building AI-powered automation for complex cloud engineering environments
• Combining platform engineering, software development and cloud expertise with modern Generative AI technologies to automate parts of the software development lifecycle

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, kubernets, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks before they become threats

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• Coordination of operations together with Data Center, IaaS and PaaS layers
• Coordination and support of network lifecycle activities including installs, upgrades, changes, and firmware updates
• Management of network interconnections and related documentation

• Technology architect with T Cloud Public hands-on experience
• Deep expertise in public cloud architecture
• Strong understanding of VPC networking
• Strong understanding of IAM & federation
• Strong understanding of cloud security architecture
• Strong understanding of Kubernetes & container platforms