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• Development of the Voice AI Agent using Python, LiveKit and WebRTC
• Ownership of end-to-end real-time voice pipelines including streaming ASR/TTS, VAD, diarization, state management, retries and latency optimization

• Odoo-modulok fejlesztése és testreszabása Python 3, XML, HTML használatával
• Backend-szolgáltatások fejlesztése Java/Spring és Hibernate segítségével
• Külső rendszerek összekapcsolása REST- és XML-RPC-API-k segítségével
• Eseményalapú integráció az Apache Kafka segítségével

• Designing scalable solutions
• Building modern user interfaces
• Developing high-performance backend services
• Writing automated tests
• Working with SQL and NoSQL databases
• Contributing across the entire software development lifecycle

• Planning and leading the technical implementation of ServiceNow solutions including system configuration and development of custom features
• Architecting and designing scalable and robust ServiceNow solutions
• Providing advanced technical consulting and support quality assurance activities

• Implementation of complex ServiceNow solutions including system configuration and custom feature development
• Provision of advanced technical consulting and support quality assurance activities
• Ensuring adherence to implementation standards and technical best practices

• 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

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• ServiceNow megoldások tervezése a jelenlegi és jövőbeli projektek üzleti, funkcionális és megfelelőségi követelményeinek megfelelően
• Szoros együttműködés a Scrum csapattal a backlog elemek átdolgozása, a követelmények tisztázása és pontos becslések készítése érdekében

• Planning and overseeing all phases of projects including discovery, development, testing, deployment, and handover
• Managing scope, priorities, milestones, dependencies, resources, quality, timelines, and budgets
• Maintaining clear and timely communication with clients and internal teams

• Drive product features end-to-end with sleek, responsive UI improvements and seamless backend integration
• Leverage agentic coding assistants and AI workflows to accelerate delivery and automate engineering tasks

• Design and evolve end-to-end architecture across data ingestion, processing, storage, and delivery
• Define scalable data pipelines and batch or near real-time workflows
• Establish efficient data models, storage strategies, and access patterns

• Definition and driving of the Quality Engineering strategy
• Design, creation and maintenance of reusable test automation frameworks
• Establishment of testing standards and best practices
• Introduction and improvement of CI/CD quality gates
• Building of E2E, integration and API testing capabilities

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain the entitlement decision cache with invalidation on entitlement changes

• Design and develop distributed backend services using .NET and event-driven architecture
• Collaborate with product and commercial teams to turn engagement ideas into scalable, maintainable, and user-friendly solutions
• Optimize microservice ecosystem for performance, reliability, and observability

• 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

• Act as the link between business stakeholders and technical teams translating business requirements into clear ServiceNow solutions
• Support clients in process analysis optimization and documentation in alignment with ServiceNow best practices

• Collaboration with customer teams to provide expert advisory services across a range of technologies
• Establishment of trusted advisor relationships with customers
• Guidance of customers towards achieving a healthy and secure state

• Assistance in developing AI-powered workflows using large language models such as Claude, GPT, and related technologies
• Support for implementation, testing, and maintenance of workflow automation solutions

• Contribution to the ID Verification ML team building in-house ML solutions
• Delivery of high-quality NodeJS, TypeScript and Python code with simplicity, performance and scalability in mind