T Hub - AI Expert

Your responsibilities, RAG System Development:, Architect and deploy end-to-end RAG pipelines, combining retrieval mechanisms (e.g., vector databases like qdrant) with generative models for enterprise use cases., Fine-tune and optimize retrieval models to ensure high accuracy and low latency in on-prem environments., Model Integration & Deployment:, Implement and customize inference servers using vLLM for efficient LLM serving and LiteLLM for lightweight model orchestration., Integrate open-source LLMs with proprietary data sources and APIs., On-Prem Infrastructure Management:, Design GPU-optimized, scalable infrastructure for LLM training and inference, ensuring compliance with security and data governance policies., Collaborate with DevOps teams to containerize workflows using Docker/Kubernetes and automate MLOps pipelines., Performance Optimization:, Apply techniques like quantization, pruning, and dynamic batching to maximize resource efficiency in resource-constrained on-prem setups., Monitor system performance, troubleshoot bottlenecks, and ensure high availability., Cross-Functional Collaboration:, Partner with data engineers to curate and preprocess domain-specific datasets for retrieval and generation tasks., Translate business requirements into technical solutions for stakeholders in telco environments.

Bachelor’s/Master’s/PhD in Computer Science, AI, or related field., 3+ years in ML/NLP roles, with 2+ years focused on RAG systems., Proven experience deploying LLMs in on-prem or hybrid environments., Proficiency with vLLM, LiteLLM, and open-source LLMs (e.g., LLAMA 3.2, Deepseek, Mistral)., Strong Python expertise with frameworks like PyTorch, Hugging Face Transformers, and LangChain., Experience with vector databases (e.g. qdrant)., Familiarity with Linux-based systems and RedHat OpenShift, Ability to communicate complex AI concepts to non-technical stakeholders., Strong problem-solving skills and adaptability in fast-paced environments.

What we offer, A dynamic environment where you’ll consecutively lead your contributions across diverse projects., Opportunity to become an expert in some of the most exciting cutting-edge technologies like Conversational AI platforms and VoIP solutions., A collaborative team setup that supports your growth in a customer-facing technical consulting role., Room for individual technological exploration while shaping innovative enterprise solutions.

Benefits, sharing the costs of sports activities, private medical care, sharing the costs of foreign language classes, sharing the costs of professional training & courses, life insurance, flexible working time, corporate products and services at discounted prices, integration events, mobile phone available for private use, no dress code, parking space for employees, extra social benefits, sharing the costs of tickets to the movies, theater, holiday funds, birthday celebration, sharing the costs of a streaming platform subscription, employee referral program, charity initiatives, extra leave, Benefit Platform

Recruitment stages, Let’s meet to better understand each other's expectations., Hiring Manager will receive your application after meeting., Technical meetings with the Hiring Manager and/or team., Time to decide!

T-Mobile, Working at T-Mobile’s T Hub will offer you an unique and highly rewarding experience on IT market. As a leader in the telecommunications industry, T-Mobile not only provides a platform to hone your technical skills but also empowers you to be a catalyst for innovation. You'll have the opportunity to work at the forefront of cutting-edge technologies, from 5G to IoT and AI, shaping the future of connectivity. Our commitment to fostering a diverse and inclusive workplace means you'll collaborate with a wide range of talented professionals, learning and growing together. T-Mobile encourages a culture of continuous learning and development, offering mentorship and support to help you thrive in your career.

This is how we work,

About the project

We seek an AI Expert with deep expertise in designing, implementing, and optimizing Retrieval Augmented Generation (RAG) systems in on-premises environments. The ideal candidate will have hands-on experience with vLLM, liteLLM, and open-source LLMs like gpt-oss or qwen, along with a proven ability to integrate these tools into scalable, secure, and high-performance enterprise workflows.

About the project

We seek an AI Expert with deep expertise in designing, implementing, and optimizing Retrieval Augmented Generation (RAG) systems in on-premises environments. The ideal candidate will have hands-on experience with vLLM, liteLLM, and open-source LLMs like gpt-oss or qwen, along with a proven ability to integrate these tools into scalable, secure, and high-performance enterprise workflows.

Your responsibilities

• RAG System Development:
• Architect and deploy end-to-end RAG pipelines, combining retrieval mechanisms (e.g., vector databases like qdrant) with generative models for enterprise use cases.
• Fine-tune and optimize retrieval models to ensure high accuracy and low latency in on-prem environments.
• Model Integration & Deployment:
• Implement and customize inference servers using vLLM for efficient LLM serving and LiteLLM for lightweight model orchestration.
• Integrate open-source LLMs with proprietary data sources and APIs.
• On-Prem Infrastructure Management:
• Design GPU-optimized, scalable infrastructure for LLM training and inference, ensuring compliance with security and data governance policies.
• Collaborate with DevOps teams to containerize workflows using Docker/Kubernetes and automate MLOps pipelines.
• Performance Optimization:
• Apply techniques like quantization, pruning, and dynamic batching to maximize resource efficiency in resource-constrained on-prem setups.
• Monitor system performance, troubleshoot bottlenecks, and ensure high availability.
• Cross-Functional Collaboration:
• Partner with data engineers to curate and preprocess domain-specific datasets for retrieval and generation tasks.
• Translate business requirements into technical solutions for stakeholders in telco environments.

Recruitment stages

• Let’s meet to better understand each other's expectations.
• Hiring Manager will receive your application after meeting.
• Technical meetings with the Hiring Manager and/or team.
• Time to decide!

Benefits, sharing the costs of sports activities, private medical care, sharing the costs of foreign language classes, sharing the costs of professional training & courses, life insurance, flexible working time, corporate products and services at discounted prices, integration events, mobile phone available for private use, no dress code, parking space for employees, extra social benefits, sharing the costs of tickets to the movies, theater, holiday funds, birthday celebration, sharing the costs of a streaming platform subscription, employee referral program, charity initiatives, extra leave, Benefit Platform

Recruitment stages, Let’s meet to better understand each other's expectations., Hiring Manager will receive your application after meeting., Technical meetings with the Hiring Manager and/or team., Time to decide!

T-Mobile, Working at T-Mobile’s T Hub will offer you an unique and highly rewarding experience on IT market. As a leader in the telecommunications industry, T-Mobile not only provides a platform to hone your technical skills but also empowers you to be a catalyst for innovation. You'll have the opportunity to work at the forefront of cutting-edge technologies, from 5G to IoT and AI, shaping the future of connectivity. Our commitment to fostering a diverse and inclusive workplace means you'll collaborate with a wide range of talented professionals, learning and growing together. T-Mobile encourages a culture of continuous learning and development, offering mentorship and support to help you thrive in your career.

This is how we work,

About the project

We seek an AI Expert with deep expertise in designing, implementing, and optimizing Retrieval Augmented Generation (RAG) systems in on-premises environments. The ideal candidate will have hands-on experience with vLLM, liteLLM, and open-source LLMs like gpt-oss or qwen, along with a proven ability to integrate these tools into scalable, secure, and high-performance enterprise workflows.