T Hub - AI Engineer (LLMs, Agents)

What Tasks Await You?

AI Model Development & Integration

• Build and develop Agentic AI- and GenAI-based solutions.
• Integrate AI models into production systems in close collaboration with other engineering teams.
• Optimize models for performance, scalability, and cost-effectiveness.

Data Preparation & Analysis

• Prepare, explore, and analyze data using Python.

Infrastructure & Platforms

• Work with on-premises, Linux-based GPU computing platforms and cloud-based instances, especially Google Cloud Platform.

Documentation

• Document technical approaches, model architectures, and implementation details.

Communication & Collaboration

• Communicate transparently with customers to set goals, identify risks and prerequisites, report progress, present results, and seek feedback.
• Collaborate with data science, POs, and IT teams to translate requirements into implementation.

What Skills Will Be Appreciated?

Experience

• Minimum 5 years in software engineering or machine learning roles with a strong AI focus.

Languages

• English proficiency at B2 level or above.
• German language skills are beneficial but not essential.

Technical Skills

Programming & Development

• Expert Python programming with strong software engineering best practices, including clean code, code reviews, testing, and production-grade deployments.
• Proficiency in software design patterns and development methodologies applicable to AI/ML projects.
• Experience with GitLab repositories, version control, and CI/CD pipelines.

Cloud & Infrastructure

• Hands-on experience with Google Cloud Platform services and managing cloud-based AI workloads.
• Skilled in working with on-premises Linux-based GPU computing environments.
• Familiarity with Docker and Kubernetes is a plus.

Machine Learning & AI

• Good understanding of supervised, unsupervised, and reinforcement learning algorithms and techniques.
• Practical experience with neural networks, including CNNs, RNNs, and Transformers, and their application in ML solutions is nice to have.
• Expertise in developing, deploying, and optimizing AI/ML models for performance, scalability, and cost-efficiency.

Generative & Agentic AI

• Strong knowledge of Large Language Models, prompt engineering, and Generative AI frameworks.
• Experience with Agentic AI frameworks such as ADK for building multi-agent systems.
• Ability to design and implement AI-driven decision-making and tool-using agents.

Data Engineering & Analytics

• Competency in SQL, data preprocessing, feature engineering, and building ETL pipelines.
• Skills in exploratory data analysis, visualization, and result interpretation.
• Experience with distributed computing frameworks for large-scale data processing.

Knowledge Graphs & Semantic Technologies

• Familiarity with Knowledge Graphs and graph databases such as Neo4j is nice to have.
• Basic understanding of data modeling, ontologies, and schema design principles.

Our Offer for You

You can look forward to working in a Network Analytics Team of artificial intelligence and machine learning experts developing advanced analytical solutions. Daily work focuses on analyzing data, developing automated tools using GenAI and ML models, and working on challenging use cases alongside software engineers and other AI engineers.

This role offers an international environment with opportunities to travel and grow. It requires flexibility to travel abroad at least three times per year for client meetings, conferences, or team off-sites, typically for 3–4 days per trip.

Benefits

• No dress code.
• Medical, sport, and life insurance packages at preferential terms.
• Access to Percipio, Coursera, and Rodos learning platforms.
• Access to products and services at preferential terms.
• Employment contract-based cooperation.
• Training or a financial bonus for recommending new employees.

What Will Your Recruitment Process Be Like?

• The recruitment process is transparent.
• The recruitment decision is based solely on an assessment of skills; race, skin color, sexual orientation, gender identity, origin, disability, political view, appearance, or religion do not influence the outcome.
• Detailed feedback is provided regardless of the outcome.
• A 20–30 minute screening meeting will cover mutual areas of interest and questions.
• The Hiring Manager receives a recommendation based on the application and screening information.
• One or two technical project meetings with the Hiring Manager and/or team members will confirm mutual fit. Meetings may last 30–90 minutes and may include the future supervisor and teammate.
• After a decision, an offer of collaboration is presented to the selected candidate. Candidates not selected receive feedback explaining the decision.