(Senior) AI Engineer - Data & AI Organisation (all genders) 1

In Merck’s Data & AI Organization, this role designs reliable analytics pipelines and enterprise-grade agentic workflows for scalable AI solutions supporting functions including Finance, HR, Procurement and Legal. The position is based in Bangalore, Karnataka, India and is full-time, with 40 hours per week.

Responsibilities

• Integrate large language models, predictive models and multi-agent frameworks into solutions using platforms such as AWS, Palantir Foundry and Snowflake. Ensure model reliability, reproducibility and performance at enterprise scale.
• Embed explainability, transparency and security in AI solutions. Use agentic engineering tools to accelerate delivery while working with Product Owners, Data Engineers and Data Scientists in agile, cross-functional Product-Oriented Delivery Teams.
• Help business teams consume AI outputs through APIs, dashboards and embedded analytics. Share knowledge, mentor peers, pilot new approaches and identify opportunities to experiment and measure impact.

Requirements

• A university degree or equivalent qualification in Mathematics, Physics, Computer Science or a related discipline; at least 5 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 processes.
• Strong Python and SQL programming; grounding in machine learning, statistics, predictive modeling and NLP; and practical experience developing LLM-powered applications. Familiarity with vector stores, reranking and LLM observability tools such as Langfuse or LangSmith, plus responsible use of agentic engineering tools in enterprise development.
• Hands-on experience with cloud or enterprise data platforms such as AWS, Palantir Foundry or Snowflake; data transformation tools such as Apache Spark, Polars, DuckDB or dbt; and MLOps and DevOps practices including MLflow, CI/CD and Docker.
• Understanding of AI applications and decision-making implications, including bias, fairness, privacy and governance. Ability to communicate complex technical concepts clearly in English and stay current with emerging AI technologies. German language skills are a plus.