Senior AI Engineer (Agentic AI)

Description

Senior AI Engineer specializing in Agentic AI. Design, develop, and deploy autonomous AI systems that support next-generation intelligent solutions and business impact across the AI lifecycle, from data to deployment.

Responsibilities

• Lead the design, development, and implementation of Agentic AI systems, including multi-agent architectures, reasoning engines, and autonomous decision-making modules.
• Collaborate with data scientists and product owners to translate complex business problems into robust, scalable AI solutions.
• Develop and optimize AI models for high performance, reliability, and interpretability within agentic frameworks.
• Design and implement data pipelines and infrastructure for training and deploying AI agents using data engineering best practices.
• Apply software engineering principles to build production-ready, maintainable, and well-documented AI systems.
• Work in an Agile environment, participating in sprints, stand-ups, and retrospectives.
• Collaborate with DevOps teams on integration, deployment, and monitoring of AI solutions in enterprise and cloud-computing environments.
• Contribute to the strategic planning and evolution of enterprise IT architecture with a focus on AI capabilities.
• Implement SQA practices for AI models and agentic systems, including testing, validation, and performance monitoring.
• Stay current with Agentic AI, machine learning, and related technologies; identify opportunities for innovation.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum 5 years of AI Engineering experience, with a strong focus on designing and implementing Agentic AI systems.
• Proven expertise in at least one major programming language, such as Python, Java, or C++, and object-oriented design.
• Solid understanding of data science principles, including machine learning algorithms, statistical modeling, and data analysis.
• Experience with cloud platforms such as AWS, Azure, or GCP, and enterprise/cloud-computing concepts.
• Experience with DevOps practices and tools for CI/CD, containerization, including Docker and Kubernetes, and infrastructure as code.
• Strong knowledge of software engineering practices, including Git, code reviews, and testing methodologies.
• Proficiency in data engineering techniques, including data warehousing, ETL processes, and big data technologies.
• Experience with Agile development methodologies.
• Familiarity with SQA processes relevant to AI and software development.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Benefits

• Project ownership and autonomy from day one.
• Dynamic work environment that encourages initiative, agility, and work/life balance.
• Ongoing coaching, mentoring, corporate training, and functional training.
• Industry certifications, including ITIL, DevOps, and MS portfolio certifications.
• Additional benefits including private health care, sport cards, in-office fitness center, stock options, saving plans, lunch subsidy, salary increases, promotion opportunities, flexible work arrangements, mentoring programs, and training.
• Opportunity to work in global, multifunctional teams across several locations and gain broad exposure to IT and product supply services.
• Hybrid work model: work from home up to two days per week, combined with in-office collaboration.
• Full-time employment contract (Umowa o Pracę) only.