Senior AI engineer
Via agency · Randstad Hungary
Software developerApplications developerSystems analystFlexibleFull-timeBudapest
We are looking for a Senior AI Engineer for our partner company specializing in international business and technology consulting to expand their team focused on generative AI developments.
Tasks
- Design, development, and deployment into production of LLM-based, RAG, and agentic systems.
- Developing technical architectures and solution patterns for generative AI applications.
- Leading complex AI solutions independently: design, implementation, quality assurance, and delivery.
- Continuously tracking and practically adapting the latest generative AI trends and research results.
- Working closely with business areas, decision-makers, and consulting colleagues to identify new use cases.
- Acting as a technical mentor: supporting medior and junior colleagues, providing professional guidance, and improving code quality.
Conditions & benefits
Flexible schedule and hybrid workCustomizable working hours and home office opportunities to maintain balance.Comprehensive benefit packageCompetitive base salary, annual performance-based bonus system, SZÉP card allowance, home office support, and private healthcare.Health and wellbeingCorporate sports opportunities, gym discounts, and various wellness programs for physical and mental recharge.Outstanding training and development opportunitiesDiverse digital and business trainings, workshops, and a stimulating environment for continuous professional development and mastering the latest technologies.Community and cultureActive social life, team buildings, company events, and a diverse, inclusive, and supportive team culture.
Requirements
- Professional experience: At least 5 years of relevant software development background, of which a minimum of 2-3 years of proven experience in developing generative AI / LLM-based systems.
- Development skills: Advanced level Python programming knowledge or confident command of another relevant language, strong OOP mindset.
- Architecture and backend: Practical knowledge of backend frameworks and microservice architectures.
- Containerization and cloud: Knowledge of containerization and orchestration technologies (Docker, Kubernetes, GitHub Actions, MLflow).
- DevOps / MLOps: Experience in designing and implementing CI/CD and MLOps pipelines in a cloud environment.
- Language skills: Confident, active English language proficiency.