Data kft állások Budapesten (it programozás, fejlesztés)

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery of data engineering, ML/MLOps, and cloud migration projects
• Managing and mentoring the data engineering team
• Building and optimizing scalable, high-performance data pipelines

• 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

• Maintain continuity of deployed products, support incident management, and assist with technical configurations
• Business process change: Understand and document current business processes, identify inefficiencies, design new to-be processes, and support business changes.

• 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

• Participation in the whole lifecycle of development projects from planning to handover
• Maintaining existing cross-platform apps
• Developing cutting-edge projects while writing high-quality code
• Keeping up with the latest technology trends
• Communicating well with other team members

• 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

• Coordination of strategic and operational initiatives across the PMO portfolio
• Management of lifecycle updates for PMO governance processes, standards, templates, and documentation
• Support of project intake, tracking, reporting, and execution activities

• Assessment and clarification of customer functional requirements related to the system/software jointly with business consultants
• Development and modification of applications or part of the application
• Preparation of related documentation

• Learn and use groundbreaking technologies.
• Engineers will apply advanced troubleshooting techniques to provide unique solutions for our customers and lead customer interactions by thoughtfully working with them to dive deep into the issue and get the root cause.

• Define and manage domain-specific architecture standards, principles, and policies aligned with enterprise standards.
• Lead tool and technology selection within the domain(s) to meet strategic objectives.

• Developing the following: Standalone Java application, CI/CD tools, Bioinformatics tools, Data visualization, Performance critical algorithms
• Ownership of specific software components and managing their life cycle.
• Supporting the development team in algorithm research and development

• 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

• Leading a global engineering organization across several teams and products within a business domain
• Setting the technical and organizational strategy
• Accountability for delivery, reliability, security, and overall performance of the organization

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• 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 and implementation of core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer...

• Design, build, review, test, and maintain Ruby on Rails features and services in line with Diligent’s agile engineering practices
• Own technical delivery for projects, epics, and major user stories, including solution design, implementation planning, and execution through to production

• Technical analysis to validate accuracy and produce data-driven results for clients
• Root cause analysis on process and data issues raised during implementation
• Design of detailed business processes and solutions in collaboration with client stakeholders

• 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

• Configuration of the P&P platform end to end, across both frontend and backend
• Tuning and optimization of forecast and attribution models to match client data and business logic
• Writing custom business logic in SQL, Python, or Go where standard configuration isn’t enough