Python programmer állások XIII. kerületben (projektmenedzsment)

Design and develop robust, scalable, and maintainable Python solutions in a modern SaaS environment, contributing to an AI-powered integration platform connecting legacy banking systems with modern digital architectures....

• Support the implementation and ongoing improvement of digital services and solutions for business customers
• Define and maintain development, testing, and operational standards to support continuous delivery
• Design, build, and maintain tools for deployment, monitoring, and operations

• AI és adatvezérelt megoldások bevezetésének, működtetésének és fejlesztésének támogatása
• AI/ML use case-ek, PoC-k és projektek szakmai koordinációja az üzleti és IT területekkel együttműködve
• Üzleti igények felmérése, technológiai lehetőségek azonosítása és a megvalósítás koordinálása

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• Making architectural decisions and conducting code reviews,
• Mentoring junior developers and leading the team,
• Designing and building scalable AI data pipelines,
• Developing LLMs (Large Language Models) and AI agent systems,
• Efficiently processing large volumes of data using Python,

• 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

• Automation and streamlining of fraud investigation processes
• Improvement of tooling for fraud investigations
• Creation of seamless experience for agents and customers during fraud investigations
• Development of innovative solutions to tackle fraud

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• The CloudOps Engineer is responsible for availability for cloud platforms
• Respond, troubleshoot and resolve production alarms
• Communicate and troubleshoot operational issues supporting a complex environment
• Respond to cloud service outages and manage incident tickets

• Leading AI-assisted software engineering activities for Meridian
• Designing repeatable SDLC patterns for analysis, validation, documentation, and evolution of complex cloud software stacks

• Ownership of backend services throughout their lifecycle including design, implementation, testing, deployment, operation, and continuous improvement
• Translation of product and business requirements into maintainable technical designs with clear communication of risks and trade-offs

• 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

• 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

• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• 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

• 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

• Management of end-to-end software release process including branch management, software version control, release note documentation, and communication with collaborators
• Driving release automation by enhancing CI/CD pipelines and defect logging and tracking for releases

• 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