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Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• 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

AI-driven vulnerability management. When frontier models can generate thousands of findings in a weekend, the bottleneck shifts from discovery to triage, verification, and remediation. We're building the pipeline that makes this sustainable....

Web alapú vállalatirányítási rendszer fejlesztése...

AI-driven vulnerability management. When frontier models can generate thousands of findings in a weekend, the bottleneck shifts from discovery to triage, verification, and remediation. We're building the pipeline that makes this sustainable....

• Design the behavioural telemetry event and entity-state schemas and write the instrumentation specification
• Own the measurement standard including canonical definitions, naming, field ownership, versioned change control

• Identify AI and automation opportunities across business processes
• Work with different departments to understand processes, pain points and repetitive activities
• Challenge existing ways of working and propose simpler, automated or completely new approaches

• 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, 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

• 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

• Lead the architecture, design, and implementation of enterprise-scale web applications using modern frontend technologies
• Serve as the technical lead for UI development while remaining actively involved in coding, design reviews, and implementation

• 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

• Leading a team of engineers to increase delivery capacity for project rollout
• Owning technical execution across frontend and full stack workstreams aligned to a scalable platform model
• Providing hands-on technical leadership in JavaScript, TypeScript and modern frontend frameworks

• Development of the Tulip OS
• Maintenance and support of bootloader, kernel, and userspace for Tulip hardware
• Working alongside product management and customers to identify key features and product performance
• Maintaining the Tulip Operating System including building, packaging, and support

• Responsibility as expert for Power Platform as a managed tool/service
• Development, support and maintenance of Power Platform solutions and connected services
• Driving SharePoint Online and Microsoft 365 migration, modernization, and transformation initiatives

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Build and evolve CI infrastructure that validates performance methodologies across cloud, on-prem, and hardware targets
• Design controlled, reproducible test environments that help distinguish real regressions from environmental noise when running and profiling targeted workloads

• Design, build, and operate the firm’s AI platform including shared services, APIs, SDKs, and tooling
• Drive architecture across scalability, reliability, security, developer experience, and cost