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Location
Hybrid (Bengaluru, India)
Seniority
Architect · 8+ years exp
Visa
Sponsors visas in United States, United Kingdom; no register of this country names it
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 15, 2026. First seen by Alion on Nov 11, 2026. GSK scores A on the Alion truth index.

Overview
Company
Impact
Profile match

GSK

GSK is a British multinational pharmaceutical company that develops and manufactures prescription medicines and vaccines, with research focused on infectious diseases, HIV, respiratory and immunology, and oncology. It was formed in 2000 through the merger of Glaxo Wellcome and SmithKline Beecham and spun off its consumer healthcare business as Haleon in 2022. Listed in London and New York, it runs research, manufacturing and commercial operations worldwide. The company is headquartered in London, England, United Kingdom.

Job Purpose:

  • GSK R&D and Digital & Tech's collective goal is to deliver GSK impact, including the acceleration of the discovery and development of medicines and vaccines to patients. The Labs and CMC Tech function is central to this mission, driving the reimagining and business transformation of our global laboratory and CMC processes. We are actively transitioning from managing raw scientific data to generating structural scientific knowledge-the foundation for how R&D will discover future medicines in a technology-enabled ecosystem.
  • The Labs CMC Data, Agentic and Knowledge Engineering (DAKE) group architects the data, agentic and knowledge foundations upon which critical R&D processes and scientific workflows depend. Crucially, our operating model relies on a hybrid workforce: AI agents function as "digital workers" to execute hands-on engineering tasks. They generate pipelines, test and deploy them, monitor them in production and remediate failures.
  • Reporting into the Director of Data and Agentic AI Engineering (G5), the Associate Director, Data & Agentic AI Engineering, leads the design of production data systems for a team and its domains within Labs & CMC. The role defines the architectural, quality, and governance standards the team and its digital workers apply, leads the team's AI-grade data infrastructure, and mentors junior and mid-level engineers.

Key Responsibilities

Domain-Level Data and Agentic Engineering

  • Design and build production data pipelines for your specific Labs and CMC domain, serving multiple downstream scientific consumers.
  • Implement, enforce and extend our team's patterns for agent-generated work, defining exactly what digital workers build and remediate autonomously versus what requires human review within your domain.
  • Integrate digital workers into your team's specific orchestration and observability workflows, applying clear guardrails, tool designs, and human-in-the-loop controls.
  • Lead the response to significant data quality incidents within your team's purview, from initial detection through to permanent resolution.

Context & Semantics Layer

  • Set the context standards for the team's Labs & CMC domains: how definitions, contracts, classification and lineage are captured in the governed context layer, so humans and digital workers can rely on them.
  • Actively contribute to the broader Labs and CMC context layer by feeding your team's hands-on operational experience upward to evolve the platform.

Data Quality & Governance

  • Execute data quality and governance standards for your team's domains, encoding them directly into the context layer so both humans and digital workers apply them by default.
  • Lead local data quality initiatives to achieve measurable outcomes, such as reduced error rates, improved audit readiness, and better downstream AI performance.

AI Data Infrastructure & Lifecycle

  • Extend our AI-grade data infrastructure for your team's specific AI system needs, including novel retrieval architectures, improved real-time data flows, and smart evaluation datasets.
  • Manage the data lifecycle for AI systems within your domain, including versioning, drift monitoring, and the governance of AI artefacts.

Platform Engineering & Mentorship

  • Design cloud data infrastructure for your team's domains, improve our Infrastructure as Code (IaC) and its deployment reliability.
  • Build shared platform components used by multiple engineers and digital workers to reduce setup time for new Labs and CMC data projects.
  • Set and enforce the code and documentation quality standards for your team, written explicitly for a hybrid workforce of humans and digital workers
  • Mentor junior and mid-level engineers through pairing, code review, and direct feedback to visibly improve their capability and independence.

Required Qualifications and Experience

Education

  • Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.
  • 8+ years of data engineering experience, including significant time leading the design and operation of complex production data systems.
  • Deep expertise with modern warehouses or lakehouses, orchestration and transformation frameworks, and batch and streaming architectures.
  • Demonstrated experience designing and operating AI agents or substantial LLM-powered tools inside data engineering workflows, including tool design, evaluation, observability and human-in-the-loop controls.
  • Experience leading the design of AI-grade data infrastructure for production AI systems, including evaluation datasets, retrieval architectures and real-time data flows.
  • Experience leading data lifecycle management for AI systems, including versioning, drift monitoring and governance of AI artefacts.
  • A track record of defining data quality and governance standards for a team or domain that others adopted, with measurable outcomes.
  • Experience leading cloud data infrastructure design with infrastructure as code.

Preferred Experience

  • Technical lead for one or more data platforms or significant domains, from first build through to scale.
  • Experience with catalogue, metadata, semantic or lineage infrastructure that AI systems consume.
  • Experience working within highly regulated industries, such as life sciences, where strict data integrity and auditability are non-negotiable mandates.

Skills

Computer Programming, Data Analysis, Data Architecture Development, Databricks Unified Data Analytics Platform, Data Engineering, Data Governance, Data Ingestion, Data Integration, Data Migrations, Data Modeling, Data Transformation, ETL Development, Performance Tuning, Structured Query Language (SQL)

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases - to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.

Please contact our Recruitment Team at [email protected] to discuss your needs.

Important notice to Employment businesses/ Agencies

GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.

It has come to our attention that the names of GlaxoSmithKline or GSK or our group companies are being used in connection with bogus job advertisements or through unsolicited emails asking candidates to make some payments for recruitment opportunities and interview. Please be advised that such advertisements and emails are not connected with the GlaxoSmithKline group in any way.

GlaxoSmithKline does not charge any fee whatsoever for recruitment process. Please do not make payments to any individuals / entities in connection with recruitment with any GlaxoSmithKline (or GSK) group company at any worldwide location. Even if they claim that the money is refundable.

If you come across unsolicited email from email addresses not ending in gsk.com or job advertisements which state that you should contact an email address that does not end in “gsk.com”, you should disregard the same and inform us by emailing [email protected], so that we can confirm to you if the job is genuine.

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