AI Engineer - Data & AI Organisation 1

AI Engineer. Location: India. Within the Data & AI Organization, a team of data enthusiasts, engineers, and AI specialists, you will design and implement reliable analytics pipelines and enterprise-grade agentic workflows that deliver scalable AI solutions across enabling functions such as Finance, HR, Procurement, and Legal. Embedding explainability, transparency, and security into every AI solution is a core expectation of this role. You will use agentic engineering tools to accelerate delivery and work closely with Product Owners, Data Engineers, and Data Scientists in agile, cross-functional Product-Oriented Delivery Teams (PODs). You will support business teams in consuming AI outputs through APIs, dashboards, and embedded analytics, while actively contributing to internal AI literacy by sharing knowledge, mentoring peers, and piloting innovative approaches. A genuine curiosity for the latest developments in AI and data science will drive you to continuously identify opportunities to experiment, measure impact, and advance the field within the organization.

You hold a university degree or equivalent qualification in Mathematics, Physics, Computer Science, or a related discipline. You bring 5 or more years of experience in data science, data engineering, analytics, or application design within a global organization, including exposure to Finance, HR, or Procurement data and business processes. You have excellent programming skills in Python and SQL, with a strong foundation in machine learning, statistics, predictive modeling, and NLP, combined with practical experience developing LLM-powered applications. You are familiar with vector stores, reranking techniques, and LLM observability tooling such as Langfuse, LangSmith, or similar, and you have experience using agentic engineering tools effectively and responsibly within enterprise software development workflows.

You have hands-on experience with cloud and enterprise data platforms such as AWS, Palantir Foundry, or Snowflake, and with data transformation frameworks such as Apache Spark, Polars, DuckDB, or dbt. You have MLOps and DevOps experience, including MLflow, CI/CD pipelines, and Docker, and you apply these practices to ensure model reliability and reproducibility at scale. You demonstrate AI literacy - a critical understanding of how AI works, its practical applications and decision-making implications, and the ethical considerations around bias, fairness, privacy, and governance - enabling you to build and deploy AI solutions responsibly. You communicate complex technical concepts clearly in English to diverse audiences; German language skills are a plus, and you stay continuously up-to-date with emerging technologies and the evolving AI landscape.