Python developer állás, munka

• Development and deployment of AI-powered applications using modern software engineering practices
• Integration of Large Language Models into business solutions
• Building scalable backend services using Python or Node.js
• Development of intuitive user interfaces with React or Angular

• Learning from senior team members
• Participation in security penetration testing projects including application-level penetration testing (e.g., web application, Android, or iOS Mobile application)
• Participation in infrastructure level security penetration testing
• Participation in Red Teaming

• 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

• Komplex AI megoldások fejlesztése ügyfelek számára
• RAG alapú megoldások fejlesztése Python/LangChain vagy Java/Spring AI technológiákkal
• Open source LLM-ek integrálása ügyfélrendszerekbe cloud és on-premise környezetben Kubernetes használatával

• Data ingestion processes from various sources into the Data Lake
• Design, development and optimization of complex data pipelines for reliable data flow
• Build, development and maintenance of frameworks facilitating construction of data pipelines

• 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

• Experience in different data science topics
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• 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, and dataset documentation

• Design, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

• Design, build, and launch AI and generative AI solutions
• Create scalable data pipelines and model deployment workflows
• Develop large-language-model and multi-agent products
• Set up automated testing, deployment, monitoring, and improvement

• 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

Ownership of detection capabilities end to end from problem framing and data through experimentation to production models and telemetry...

• Építés agentic rendszerek tool-using munkafolyamatokkal, RAG, strukturált kimenetek, guardrails és mérhető minőség
• Együttműködés Solution Architect-ekkel és LLMOps-szal
• Fejlesztés megbízható és folyamatosan fejlesztett rendszerekben

• Új technológiák bevezetése
• Termékfejlesztési és szolgáltatási igények implementálása
• Rendszerintegrációk megvalósítása
• Rendszertervezés
• Tesztelés
• Dokumentálás
• Együttműködés solution architektekkel és rendszerszervezőkkel alkalmazás- és interfészfejlesztések terén
• Minőségbiztosítási feladatok támogatása

• 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

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

• 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

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Tesztmenedzsment feladatok vezetése a teljes tesztfolyamat szakmai kísérésével az igényfelméréstől a riportolásig
• Követelményanalízis fejlesztőkkel, üzemeltetőkkel és más érintettekkel közösen
• Tesztstratégiák tervezése és tesztelési lépések meghatározása és követése