Plattform AI Engineer

Tasks:

• Design and implement reusable framework components for agentic AI systems, including schemas, contracts, automated tests, and documentation
• Create Architecture Decision Records and arc42 documentation, including rejected alternatives
• Establish evaluation procedures for agentic workflows, including test cases, quality metrics, comparison datasets, and reassessment after model changes
• Implement blocking quality gates in GitLab CI/CD pipelines
• Maintain a versioned and searchable component registry and define a contribution process for other teams
• Assess teams’ enablement needs and provide training, workshops, guided use‑case sessions, hackathons, office hours, and demonstrations
• Train teams in the tool stack, AI tools, agentic working methods, quality assurance, limitations, and common AI failure modes
• Create and maintain training materials, guidelines, reusable examples, and reference cases
• Support teams until they can use the framework independently and act as a contact for user questions
• Evaluate new tools, models, and methods through limited trials with documented results
• Coordinate with Architecture, Security, Data Protection, Compliance, and Operations
• Participate in backlog refinements and ART planning, including effort estimation and task slicing
• Ensure compatibility across macOS, Linux, and Windows environments
• Monitor the costs and runtimes of agentic workflows and recommend suitable alternatives
• Define how AI-generated changes are created, reviewed, documented, and validated by humans
• Contribute to the technical and strategic direction of the framework and improve quality and abstraction levels across the team

Required skills:

Must haves:

• Very good understanding of agile working methods and the end-to-end software development lifecycle
• Practical experience with MCP servers and agentic skills
• At least 12 consecutive months of hands‑on experience using AI tools in software development, such as Kiro CLI, GitHub Copilot, Claude Code, Cursor, or equivalent
• Several years of experience in IT consulting and knowledge transfer
• Strong understanding of LLMs, context windows, embeddings, RAG, tool calling, agents, orchestration, guardrails, prompt injection, evaluation, hallucinations, and token costs
• Ability to identify AI limitations and failure modes and derive appropriate implementation decisions
• Ability to present a case where an AI-supported approach was unsuitable and explain the resulting decision
• Ability to explain technical solutions so that other teams can use them independently
• Practical Scrum experience, including backlog work, vertical task slicing, Definition of Done, and Jira
• Ability to design reusable abstractions instead of isolated solutions
• Strong user focus when designing framework components
• Reliable delivery in an agile team and the ability to break down complex initiatives into implementable steps
• Constructive, evidence-based decision‑making and the ability to work effectively with incomplete information
• Proactive learning mindset and willingness to share knowledge
• Strong communication, moderation, analytical, teamwork, and assertiveness skills

Nice to haves:

• Experience in large, regulated IT organizations
• Experience improving agentic systems through evaluations
• Cloud experience, preferably in an organization using the SAFe framework
• Experience defining quality metrics and comparison datasets for agentic workflows
• Knowledge of AWS Bedrock AgentCore, Microsoft Foundry Agents Service, and Microsoft Copilot Studio
• Experience in the railway sector or a comparably complex corporate environment with Security, Data Protection, and Compliance requirements
• Previous experience within the Deutsche Bahn Group