AI backend engineer in rail mobility

Siemens Mobility is a leading provider of innovative mobility products and solutions, covering the full rail asset lifecycle through hardware, software, and services. Our mission is simple but ambitious: help customers make better decisions by turning IoT data from rail assets into reliable, actionable insights! As a AI Backend Engineer, you will play a key role in transforming real user needs across Siemens Mobility into scalable, production‑grade AI services.

• working closely with internal stakeholders, understanding their workflows in depth, and identifying where AI can genuinely add value.
• These insights are translated into AI‑enabled service designs that go far beyond prototypes and make it into daily use.
• Prompt engineering is treated as a structured discipline, supported by measurable evaluation strategies and high‑quality datasets.
• there is an active role in mentoring junior engineers and working students, guiding them through experiments, evaluation methods, and continuous improvement.
• building and operating production AI services using LLMs, RAG and hybrid retrieval approaches, and vector search technologies.
• Features are owned end‑to‑end—from design and implementation to deployment, monitoring, and ongoing improvement—within modern CI/CD and software quality standards.

• A degree in Computer Science, IT, or a related field is expected, along with 5+ years of hands‑on experience in AI, NLP, or Information Retrieval.
• Experience bridging exploratory data science (CRISP‑DM) with structured software development (SDLC) is essential, especially when turning experimental work into reliable, deterministic releases.
• Advanced Python (3.11+), including async/await, type hints, and Pydantic
• Production‑level software practices: testing with pytest, code quality enforcement (ruff, mypy, pre‑commit), and structured Git workflows
• Strong autonomy in development environments, including Docker and local tooling
• Deep understanding of LLMs, NLP, and prompt engineering
• Hands‑on experience with RAG, hybrid retrieval, GraphRAG, vector search (e.g., OpenSearch)
• Experience designing automated evaluation pipelines for AI quality and retrieval performance
• Будет плюсом: Experience with cloud AI platforms such as AWS Bedrock or Azure OpenAI, and familiarity with Model Context Protocol (MCP) or modern API interface standards, are valued extras

• A flexible working model to promote a better work-life balance, a health insurance and access to our on-site medical center.
• 2 volunteering days a year and 4 additional bridge days per year.
• In addition, you’ll have access to exclusive discounts on Siemens and Bosch brands, and access to Siemens Learning Platforms that allow for internal online courses, as well as external platforms such as Coursera, Udemy, and LinkedIn Learning.