Technical állások Budapesten (it programozás, fejlesztés)

• Develop and maintain Java-based backend applications and services.
• Design and implement REST APIs and backend integrations.
• Develop and integrate Camunda-based business process workflows.
• Build and maintain solutions within a distributed system landscape.

• Leading and mentoring a cloud engineering team of 5-7 cloud engineers
• Providing direct line management, coaching, and professional development for a team of cloud engineers and migration specialists
• Fostering a high-performing, technically excellent team focused on secure and scalable migrations

• Deployment and scaling of EcliptOS platform
• Ownership of EcliptOS platform delivery lifecycle
• Deployment and configuration of production-grade systems across cloud and hybrid infrastructures
• Validation of performance and stability of deployed systems
• Ensuring structured handovers for long-term success

• Design and development of innovative AI solutions
• Collaboration with global technologists, data scientists, and industry experts
• Development of scalable data pipelines
• Building software products and services from the ground up
• Assessment of data landscapes and ensuring data quality

• Engineering execution across the Veeva Platform ecosystem
• Translation of platform engineering strategy into executable plans and measurable outcomes

Design, deploy, and maintain observability platforms and tools such as Prometheus, Grafana LGTM+ stack, OTel and others...

• Design and implementation of web user interfaces using Angular and TypeScript.
• Independent development of clean, reusable UI components based on rds-ng libraries.
• Integration of backend services through generated API clients (OpenAPI/TypeScript, contract-first approach).

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• High-performance simulation loops, autonomous behavior, and data-oriented design
• Improve system performance, proactively indetify technical debt
• Understanding and optimize complex dataflows
• Designing, improving, extending existing architecture
• Create technical specification based on business needs

• Collaboration with a global network of technologists, designers, and strategists
• Development of cutting-edge products
• Mentoring client teams
• Shaping engineering cultures
• Development of software products and services from the ground up

• Design and build innovative AI solutions combining advanced software development and data engineering
• Collaborate with global technologists, data scientists, and industry experts to transform businesses through advanced analytics and AI-driven solutions

• Build, maintain, and enhance cybersecurity reporting solutions, dashboards, and analytics using Cognos and Tableau.
• Collect, analyze, and transform cybersecurity risk and performance data into actionable insights and metrics.

• Managing complex database systems within a global technology ecosystem
• Building and managing database hosting capabilities using Infrastructure as Code for all platform needs
• Building database infrastructure platforms with developers and providing guidance and tooling to handle distributed systems

• Design, implement, and optimize machine learning models to solve complex business problems
• Oversee the entire machine learning lifecycle, from data collection and pre-processing to model deployment and monitoring

• Building and leading McKinsey's forward-looking capabilities to transform clients' innovation engines
• Bringing distinctive statistical knowledge to complex client Life Sciences R&D challenges through part-time staffing on client studies with a multi-disciplinary team

• Design, build and deploy AI and agentic solutions with real business impact
• Design, build and deploy LLM-powered pipelines and autonomous agents
• Work closely with stakeholders to scope and deliver solutions
• Set best practices around MLOps and production-grade AI

• 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, governance, deployment, and ongoing enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle, including prioritizing initiatives, influencing roadmap decisions, and ensuring successful deployment into production

• Management of player accounts including account creation, verification, updates, and closure
• Account authentication, controls, and security
• User session management
• Responsible gaming

• Problem-solving on key issues with C-suite executives
• Providing actionable recommendations
• Working across a broad range of client topics, industries, and functions