Python developer állások VIII. kerületben (it tanácsadó, elemző, auditor)

Assess and document downstream impact of Skills and Job Architecture data quality issues across payroll processing, management reporting, third-party integrations, and AI/machine learning model inputs...

• Working with cutting edge technology enabling Cloud Journey
• Managing Infrastructure as Code for parts of Core Platform Layer including Kubernetes Clusters, Message Broker backends, Infrastructure tooling

• Be able to manage small teams to deliver analytic functions in support of strategic and business development projects.
• Analyse and assess macroeconomic, energy market and other industry-specific developments by synthetizing available empirical evidence, related literature, and economic theory.

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Architect cloud-native AI applications integrating LLMs vector search and real-time data
• Design end-to-end web solutions from frontend to backend
• Implement RAG pipelines model serving and AI agents in production
• Lead cross-functional teams (Full-stack AI Data)

• Komplex üzleti folyamatok végpontok közötti automatizálása Java és Spring Boot alapokon
• Automatizációs megoldások fejlesztése UI és API szinten Selenium, LeanFT és hasonló eszközök bevonásával
• AI-alapú prototípusok, belső eszközök és automatizációk fejlesztése kontrollált vállalati környezetben

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Service-level analysis of modular cloud software
• Mapping APIs, configuration flows, service dependencies, database usage, and operational assumptions of OpenStack-style services and surrounding components

• Lead AI-assisted software engineering activities for Meridian by designing repeatable SDLC patterns
• Anchor the engineering approach for OpenStack-derived services, repository-scale understanding, and sovereign software handover readiness

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