Generative AI/Agentic AI Engineer (d/f/m) [26084] at Sopra Steria

Ulm, Baden-Württemberg, Germany -

Full Time

Start Date

Immediate

Expiry Date

22 Jul, 26

Salary

0.0

Posted On

23 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, GenAI, LLM, RAG, MCP, Docker, Kubernetes, Vector databases, Qdrant, Chroma, CI/CD, Cybersecurity, Git, Chatbots, Autonomous agents

Industry

Information Technology & Services

Description

Company Description CS GROUP, together with HE Space and Sopra Steria, has been successfully providing digital end-to-end systems and engineering services for more than 40 years. With over 2000 employees worldwide, we combine advanced and unique skills in both information technology and space data engineering. We combine entrepreneurial agility with cutting-edge technological expertise. CS GROUP is a leading provider of operational systems and an important and trusted long-term partner for space and defence organisations. At CS GROUP, we are driven by innovation and we value our most important asset: our people. Job Description The area of responsibility is detailed as follows: Development & Implementation: Design, coding, orchestration, and testing of scalable GenAI services, chatbots, and autonomous agents using modern frameworks On-Premise Operation & Hosting: Deployment and maintenance of LLM infrastructures in our secure on-premise environment (Docker/Kubernetes), including performance optimisation and resource management Security & Compliance: Ensuring that all developments comply with the strict security guidelines of Airbus Defence and Space RAG & MCP: Development and optimisation of RAG pipelines for connecting internal knowledge databases as well as implementation of MCP tools for standardised, secure interfaces between AI models and internal tools/data sources Technical Support & Enablement: Support for internal users, troubleshooting, as well as creation of technical documentation and best practices for the development team Active participation in the technical roadmap through proofs-of-concept (PoCs) for new AI use cases Qualifications You will have the following qualifications and relevant experience: Bachelor's Degree in Computer Sciences, Data Science or similar; Professional Experience Experience with RAG architectures and MCP should be present Knowledge of CI/CD pipelines is a great advantage Experience with logging & monitoring stack in the server area is an advantage Basic knowledge in cybersecurity for AI systems IT Skills Python: at least knowledge of detailed functions GenAI Expertise: Proven experience in developing LLM applications, chatbots, and agents. Experience with inference frameworks (vLLM, SGLang, etc.) is required Experience with vector databases (Qdrant, Chroma, etc.). Experience in using AI agents (Claude Code, OpenCode, etc.). Staying up-to-date with all developments in the AI field (skills, sandboxing, etc.) is absolutely necessary Infrastructure & DevOps: At least good experience with Docker and Kubernetes (deployment, scaling, monitoring) in on-premise environments required Network Basics: Understanding of network concepts in container environments is desirable Version Control: Confident use of Git (branching strategies, code reviews) is a great advantage Language Skills German, at least business fluent English , at least proficient Additional Information This job is located in Ulm, Germany. If you think you have what it takes for this job, please send your CV (in English) by clicking on the button “I'm Interested" An exciting and dynamic international working environment awaits you! Inclusive and committed employer, our company works every day to combat all forms of discrimination and promote a respectful working environment. That's why, committed to gender diversity and overall inclusivity, we encourage all applications and profiles. Last apply date: 05-05-2026!

Responsibilities

You will design, code, and deploy scalable GenAI services, chatbots, and autonomous agents within a secure on-premise environment. Additionally, you will optimize RAG pipelines and implement MCP tools to ensure secure interfaces between AI models and internal data sources.