Principal Engineer, Data & Agentic AI Engineering
GSK (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Own and manage end-to-end Labs & CMC data domain pipelines, models, and datasets, ensuring quality and audit-readiness.
- Design and improve frameworks and tools enabling AI digital workers to autonomously build, test, deploy, monitor, and remediate scientific data workflows, aiming for reduced manual interventions.
- Develop and maintain data quality frameworks, governance documentation, and AI data infrastructure to support production AI systems within a regulated life sciences environment.
Minimum Requirements
- 6+ years experience building and operating production data pipelines and models.
- Strong expertise in SQL, Python, and modern data warehouses/lakehouses (e.g., Databricks, BigQuery) with orchestration tools like Airflow, dbt, or Spark.
- Experience designing and operating AI agent/LLM tools in data workflows, including feature stores, vector databases, data contracts, and managing AI training/evaluation datasets.
- Bachelor's degree in Computer Science, Data Engineering, or related field, or equivalent practical experience.
Ideal Candidate Profile
- Proven ability to independently design and operate complex scientific data domains and data infrastructure in regulated or high-stakes environments such as life sciences or healthcare.
- Experienced in applying data governance, privacy, IP, and compliance controls in AI-enabled data pipelines with strong focus on auditability and quality assurance.
- Skilled at improving AI digital worker autonomy through iterative enhancement of frameworks, tooling, and quality evaluation signals in a hybrid human-digital workforce setting.