Sonrisa Technologies

• Working in agile development team • Being a refactoring and unit testing junkie • Being a fan of clean, object-oriented code and code review • Research cutting edge technologies

• Working on international, diversified, greenfield projects • Understanding full software development life cycle • Being professional in functional and non-functional testing • Good sense for understanding business problems and finding potential error case

• Build a bridge between the client and the development team • Requirement analysis and management • Defining product backlog and specifying user stories • Gap analysis • Understanding the business goals • Discovering and mapping end-to-end process flows, including identifying opportunities for AI enhancement • Be responsible for meeting business goals • Lead the backlog refinement and participate in sprint planning, demo, and retrospective sessions • Supporting the testing process by providing guidance to the QA colleagues • Build a good working relationship with clients • Foster agile and lean best practices with a continuous development mindset • Translate client business problems into AI-addressable solutions and support feasibility assessments for AI components • Contribute to presales engagements with input on AI solution scoping and effort estimation

• You'll be working on international, diversified, greenfield projects • Being desperately passionate for technology and software quality • Understanding full software development life cycle • Being professional in functional and non-functional testing • Good sense for understanding business problems and finding potential error case

• Work in hybrid engineering teams • Setting direction and technical strategy • Quality assurance and validation of AI-assisted outputs • Managing client relationships • Guide implementation combining hands-on development with AI-assisted execution • Identify opportunities where AI can accelerate delivery

• Develop AI-powered applications: chatbots, RAG systems, voice agents, and agentic workflows • Implement LLM integrations using foundation model APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google AI) • Build and optimize RAG pipelines: document processing, chunking, embedding, and retrieval • Apply prompt engineering and context engineering techniques to optimize LLM behavior and output quality • Integrate AI capabilities into existing software systems • Implement observability and monitoring for AI applications • Write clean, maintainable, well-documented code following best practices • Develop tests, participate in code reviews, and debug AI application issues • Optimize AI solutions for performance, cost, and reliability • Follow established coding standards and development workflows • Work with AI Solutions Architects to implement technical specification • Collaborate with project teams and QA to deliver quality solutions • Participate in agile ceremonies and provide effort estimates • Stay current with AI tools and contribute to knowledge sharing

• Managing client accounts • Providing IT analysis and consultancy with the help of IT experts • Developing business relationships • Resource and revenue forecasting • Driving sales in Hungary and Europe • Day-to-day communication with clients and internal teams to ensure successful project delivery and client satisfaction

• Be the key technical leader responsible for designing the overall software architecture. • Ensure the delivered solution is effective, scalable, and meets all business requirements. • Bridge the gap between business needs and technical implementation. • Lead the planning of development lifecycles. • Conduct Functional and Technical Analysis of existing live systems. • Specify the requirements for development/test environments. • Ensure new software components are designed for easy testability. • Conduct Architect Reviews as part of the quality assurance process. • Serve as a Great Communicator and technical consultant to stakeholders. • Provide Effort Estimation for all roles.

• Build a bridge between the client and the development team • Requirement analysis and management • Defining product backlog and specifying user stories • Gap analysis • Understanding the business goals • Discovering and mapping end-to-end process flows • Be responsible for meeting business goals • Lead the backlog refinement and participate in sprint planning, demo, and retrospective sessions • Supporting the testing process by providing guidance to the QA colleagues • Build a good working relationship with clients • Foster agile and lean best practices with a continuous development mindset

• Participate in active client AI projects as the hands-on AI specialist • Design and build AI agent workflows, prompt chains, and orchestration logic • Develop and refine prompts for specific business use cases (prompt engineering) • Analyze existing client workflows and identify opportunities for AI enhancement • Create working prototypes and proofs-of-concept to validate approaches • Collaborate with developers on implementation handoff and technical specifications • Support presales engagements with AI solution proposals and feasibility assessments • Conduct business domain analysis to identify where AI creates genuine value • Translate client business problems into AI-addressable solutions • Prepare demonstrations and prototype artifacts for client presentations • Provide input on effort estimation for AI components of proposals • Monitor AI news, model releases, tool updates, and emerging techniques • Evaluate new AI platforms, frameworks, and services for potential adoption • Experiment with new approaches and share findings • Document patterns, techniques, and lessons learned from project work • Contribute to internal knowledge bases and training materials • Design agentic workflows using orchestration frameworks (e.g., n8n, LangGraph, custom pipelines) • Optimize existing business workflows by introducing AI capabilities • Define conversation flows, tool usage patterns, and handoff logic for AI agents • Specify context management, memory strategies, and retrieval patterns