Aws cloud engineer állások, munkák

• Új backend alkalmazások és funkciók fejlesztése Java és kapcsolódó technológiák segítségével
• RESTful API-k tervezése és megvalósítása, amelyek hatékonyan kommunikálnak az adatbázisokkal
• A teljes fejlesztési életciklusban való aktív részvétel: tervezés, fejlesztés, tesztelés és telepítés

• Ownership of features from concept to delivery
• Writing precise specifications
• Working closely with teammates and stakeholders to refine requirements
• Driving work through to production with full accountability

• NET alkalmazások fejlesztése és karbantartása C# és .NET Core technológia használatával
• RESTful API-k és mikro-szolgáltatások fejlesztése
• Adatbázisok kezelése és optimalizálása (pl. SQL Server, PostgreSQL, NoSQL)
• Szoftverek teljesítményének javítása és hibák keresése
• Meglévő kódok refaktorálása

• Translate business requirements into technical solutions through workshops, prototyping, and iterative delivery
• Collaborate with customers across the delivery lifecycle (workshops, reviews, UAT) to refine and optimize solutions

Design and Own End-to-End Solutions: Lead the architectural design and implementation of high-availability, high-performance backend services and platform components, seeing them through from concept to production completion....

• Leading a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Providing mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Developing highly scalable services realizing AI/ML functionalities

• Ownership of features from concept to delivery
• Writing precise specifications
• Working closely with teammates and stakeholders to refine requirements
• Driving work through to production with full accountability
• Working with AI as a first-class collaborator

• Building secure, scalable serverless microservices and AI-powered features using TypeScript and React on AWS for the Risk Manager platform
• Owning and delivering well-defined stories independently with a clear grasp of team architecture, frameworks, and tools

• Building and evolving the Risk Manager platform
• Developing secure, scalable microservices using TypeScript and React in a serverless architecture on AWS
• Contributing to AI-powered features for risk management
• Taking end-to-end ownership of services from development to deployment and monitoring

• 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

Discussion, dispute, planning, design and implementation of best practice AWS architectures based on client requirements...

Customer-Focused Outcomes: As a Senior SAP AI Engineer (f/m/d), you will be a key driver of customer value delivery, translating SAP AI architectural blueprints into fully functional, scalable, and production-ready solutions. Specifically, you will:...

• Lead the technical lifecycle of ServiceNow and related governance platforms (IRM, Risk, Change, Incident, CMDB, Asset).
• Ensure configurations are secure, scalable, auditable, and aligned with regulatory standards.

• Development of integrated automated tests
• Creation of automated test reporting and metrics collection
• Transition of testing from manual to automated approach
• Maintenance and refactoring of testcases
• Collaboration and knowledge sharing with QA Team members and Software Developers

• Leading and growing multiple agile engineering teams
• Defining and owning the technical roadmap with stakeholders
• Championing responsible use of AI and automation
• Aligning technical strategy with business goals
• Mentoring and coaching engineers at all levels

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Development of highly scalable services realizing AI/ML functionalities
• Implementation of machine learning solutions for computer vision and NLP use cases
• Work with Large Language Models (LLMs) and perform prompt engineering tasks

• Rendszertervezés
• Hibaanalízis és javítás
• Optimizációs javaslatok kidolgozása és megvalósítása
• Unit tesztek és integrációs tesztek végrehajtása, automatizálása
• Termékfejlesztési folyamat irányítása
• Üzleti és termékcélok megértése, alkalmazások felügyelete

• Operation and support of Global Directory (LDAP) services across multiple environments
• Manual data maintenance and user management
• Manual interventions such as copying users between environments and maintaining directory data consistency

• Outbound and inbound lead generation campaigns execution through HubSpot and LinkedIn Sales Navigator
• Research and identification of potential clients in target industries such as IT services, fintech, manufacturing, and enterprise transformation