Staff Data Engineer — AI Context & Pipelines

GlaxoSmithKline; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

GlaxoSmithKline (GSK) seeks a Staff Data Engineer to own and evolve the governed context layer used by humans and AI agents across Enterprise AI. You will define architecture standards, build data infrastructure for AI, and ensure data governance and security throughout production pipelines.

You will lead in designing scalable, cloud-based data platforms with IaC, establish MLOps practices, and mentor senior engineers while collaborating with cross-functional teams to enable safe, scalable AI

Qualifications

• Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.
• 10+ years of data engineering experience, including experience defining data architecture for production AI or machine learning (ML) systems.
• Experience building data infrastructure for AI systems, including feature stores, vector databases, retrieval architectures, streaming data pipelines and evaluation datasets.
• Experience building context, metadata or semantic infrastructure used by AI systems, such as data catalogues, business glossaries, knowledge graphs or ontologies, exposed to AI agents through protocols such as Model Context Protocol (MCP).
• Experience designing and operating AI agents or large language model (LLM)-powered systems within data workflows, including evaluation, guardrails and human-in-the-loop controls.
• Experience defining data quality, lineage and governance standards for AI pipelines across multiple data domains, including privacy, consent, personally identifiable information (PII) handling and auditability.
• Experience with cloud data platforms and infrastructure as code, including experience setting engineering standards.

Responsibilities

• Owns the governed context layer as the shared foundation every human and digital worker in EAI relies on, accountable for its architecture, implementation and evolution.
• Defines the architecture standards and shared frameworks that digital workers use to generate, test, deploy and monitor pipelines, reducing the integration cost of each new AI initiative.
• Set the operating model for agent-generated engineering work: what digital workers do autonomously, what requires human approval, how quality is evaluated and how incidents elevate.
• Shape EAI's AI data infrastructure strategy across feature engineering, vector and retrieval infrastructure, streaming data flows and evaluation data design.
• Define EAI's MLOps data practices: versioning, lineage, drift monitoring, evaluation dataset governance and model data lifecycle management, extended to the context and evaluation data that digital workers rely on.
• Define EAI's responsible data governance standards for AI pipelines, covering privacy, consent, PII, auditability and bias controls, and encode them in the governed context layer so humans and digital workers apply them by default.
• Design EAI's data platform architecture with infrastructure as code throughout and platform-as-product thinking, so new data and AI projects start quickly and consistently.

Skills

Computer Programming

Data Analysis

Data Architecture Development

Databricks Unified Data Analytics

Data Engineering

Data Governance

Data Ingestion

Data Integration

Data Migrations

Data Modeling

Data Transformation

ETL Development

Performance Tuning

SQL

Education

Bachelor's degree in Computer Science, Data Engineering or a related field

Job description

GlaxoSmithKline (GSK) seeks a Staff Data Engineer to own and evolve the governed context layer used by humans and AI agents across Enterprise AI. You will define architecture standards, build data infrastructure for AI, and ensure data governance and security throughout production pipelines.

You will lead in designing scalable, cloud-based data platforms with IaC, establish MLOps practices, and mentor senior engineers while collaborating with cross-functional teams to enable safe, scalable AI