Python developer állások Martonvásárban középiskolai végzettséggel

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale

• Technical leadership for digital solution Navify Cervical Screening
• Driving architectural decisions
• Overseeing data integration
• Ensuring delivery of features and improvements
• Providing orchestration within cross-functional agile product teams

• Design, develop, and maintain multimedia middleware components
• Build, integrate, and optimize GStreamer-based audio/video pipelines
• Integrate media components with user-space applications and system services
• Debug and resolve complex media issues related to performance, stability, and synchronization

Performing tasks related to the position....

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• 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 including Full-stack, AI, and Data

• Owning the infrastructure that keeps the PKI running
• Designing and maintaining Terraform modules across multi-cloud environments
• Operating Kubernetes in a hybrid setup
• Running secrets and PKI plumbing
• Improving CI/CD pipelines in GitLab CI and GitHub Actions
• Maturing ArgoCD-based GitOps

• Owning technical architecture and design decisions for Secure Account Management (SAM) cloud platform
• Translating security architect guardrail requirements and security standards into implementable engineering work
• Designing reusable, self-service modules and APIs for platform consumers

• Design, develop, and maintain scalable data pipelines in cloud and hybrid environments
• Contribute to the architecture of enterprise data platforms with a system-oriented mindset
• Work with large-scale datasets using SQL, Spark, and cloud-native tools

• 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 including Full-stack, AI, and Data

• Defining the vision and strategy for the future-state digital supply chain ecosystem
• Curating the technology stack through selection and integration of modern tools at the crossroads of artificial intelligence and automated workflows

• Funkcionális specifikációk technikai tervezése
• Alkalmazás- és rendszerarchitektúra kialakítása
• Skálázható és karbantartható full-stack fejlesztés: adatbázis, backend, frontend, API-k és külső integrációk megvalósítása
• Deploy és üzemeltetés előkészítése (konténerizálás, CI/CD, cloud)

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients’ technical teams
• Solution design and configuration of data labeling and processing pipelines

• PEGA alacsony kódszintű alkalmazásfejlesztés eset típusok, munkafolyamatok és üzleti folyamatok modellezése és megvalósítása a PEGA Platformon
• Újrafelhasználható komponensek készítése több alkalmazásban is felhasználható funkcionális modulok fejlesztése

• Delivery of complex data engineering projects
• Leading small delivery teams
• Management of customer relationships
• Supporting pre-sales processes
• Mentoring junior engineers
• Contributing to hiring data talent

• Delivery of complex data engineering projects across industries
• Leading small delivery teams
• Management of customer relationships individually or with a Project Manager
• Support of pre-sales process
• Mentoring of junior engineers
• Contribution to hiring data talent

• Setting the technical direction for AI-enabled platform
• Architecting secure, scalable, serverless systems on AWS
• Defining patterns and governance practices for multiple teams
• Guiding AI value addition across the stack
• Mentoring senior engineers
• Leading org-wide design decisions