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Senior principal software engineer - r&d tech

London
GSK
Principal software engineer
€150,000 - €200,000 a year
Posted: 22 January
Offer description

Location: UK – London – New Oxford Street, India - Karnataka - Bengaluru, USA - Pennsylvania - Upper Providence

Posted Date: Jan 19 2026

GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centered on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems.

Our diverse portfolio consists of vaccines, specialty medicines, and general medicines. Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.

About R&D Technology
R&D at GSK is highly data‑driven, and we’re applying AI/ML and data engineering to generate new insights, enable analytics, gain efficiencies and automation. This role is in R&D Technology where you’ll architect and build production‑grade applications and data platforms. You’ll work on diverse projects spanning regulatory, clinical, legal and HR domains. Versatility is key, with an ability to quickly understand domain data and requirements and translate them into robust technical solutions. You will interact with architects, software and data engineers, AI/ML modelers, product owners as well as other team members across R&D. You will actively participate in creating technical solutions, designs, implementations and participate in the relentless improvement of R&D Tech systems in alignment with agile and DevOps principles.

In this role you will have the opportunity to work on a mixture of the following:
Software Engineering & Application Development

Write production‑grade code for full‑stack applications using Python and modern frontend frameworks

Build and maintain scalable REST APIs and microservices architectures

Design application architectures and implement technical solutions

Develop user interfaces and data visualization components

Write comprehensive tests and ensure code quality

Debug and optimize application performance

Cloud Architecture & Services

Design and architect cloud‑native applications and solutions on Azure

Leverage Azure services including App Services, Azure Functions, AKS, Storage, Data Factory, Cosmos DB

Implement scalable, resilient, and cost‑effective cloud architectures

Optimize cloud resource utilization and performance

Design for high availability, disaster recovery, and security

Implement cloud security best practices and governance

Data Engineering

Build and maintain data pipelines for large‑scale data processing

Implement ETL/ELT processes for diverse data sources

Optimize data workflows and processing performance

Design and implement data models and schemas

Work with structured and unstructured data at scale

AI/ML & GenAI Integration

Integrate AI/ML models and APIs into production applications

Build GenAI applications using LLMs and frameworks like LangChain

Implement RAG (Retrieval Augmented Generation) architectures

Work with vector databases for semantic search capabilities

Apply prompt engineering techniques for optimal LLM performance

Understand and implement basic NLP tasks (text classification, entity extraction, embeddings)

Collaborate with data scientists to productionise ML models

Evaluate and integrate new AI/ML technologies

Database & Data Management

Write SQL queries for data analysis and application needs

Design and optimise database schemas for both relational and NoSQL databases

Tune query performance and implement indexing strategies

Implement data access patterns and ORM frameworks

DevOps & Infrastructure

Implement Infrastructure as Code and CI/CD pipelines

Containerise applications and orchestrate deployments with Docker and Kubernetes

Implement monitoring, logging, and alerting solutions

Automate deployment and operational processes

Ensure application scalability and reliability

Cross‑team Collaboration

Work closely with data scientists, engineers, and product owners across R&D

Participate in code reviews and knowledge sharing

Contribute to technical discussions and solution designs

Identify innovations and architect solutions

Evaluate and integrate new technologies

Basic Qualifications

Bachelor's degree in Computer Science or equivalent relevant industry experience

Significant hands‑on software development experience with demonstrated progression in technical complexity

Expert‑level Python programming with extensive production application development experience

Strong full‑stack development experience with modern frameworks (Backend: Python – FastAPI, Flask, Django; Frontend: React, Next.js, TypeScript or similar)

Cloud services experience, preferably Azure (App Services, Functions, Storage or equivalent)

Strong SQL skills: Writing complex queries, data modelling, and optimisation

Data engineering fundamentals: Building data pipelines and working with large datasets

Understanding of AI/ML concepts and practical experience (Familiarity with LLMs and GenAI applications; Basic understanding of how to integrate AI/ML APIs into applications; Knowledge of prompt engineering basics; Understanding of RAG architectures or willingness to learn quickly)

Experience building production‑grade applications: Scalable, maintainable, well‑tested code

Understanding of software architecture: Design patterns, microservices, distributed systems, cloud‑native architectures

Version control with Git and collaborative development workflows

DevOps practices: CI/CD pipelines, containerisation basics

Agile development practices and iterative development

Excellent problem‑solving and debugging skills

Strong communication and collaboration skills

Ability to quickly learn and adapt to new technologies

Highly Desired Skills

Azure cloud platform expertise: Deep knowledge of Azure services (App Services, Azure Functions, AKS, Storage Accounts, Azure Data Factory, Cosmos DB, Azure SQL, Key Vault, Application Insights)

Cloud architecture and design: Designing scalable, secure, and cost‑effective cloud solutions

Databricks and Apache Spark for large‑scale data processing

Hands‑on experience with GenAI platforms (OpenAI, Azure OpenAI, LangChain or similar)

Experience building RAG applications with chunking, vectorisation, retrieval strategies

Vector databases (pgvector, Pinecone, Weaviate or similar)

DevOps maturity: Infrastructure as Code (Terraform, Bicep, ARM templates), advanced CI/CD

Containerisation and orchestration: Docker and Kubernetes (AKS)

Database expertise: PostgreSQL, SQL Server, Azure SQL with performance tuning

Cloud security: Identity management, RBAC, network security, encryption

Azure DevOps or GitHub Actions for CI/CD pipelines

Experience with REST API design and microservices patterns

Preferred Qualifications

Azure certifications (Azure Solutions Architect, Azure Developer, Azure Data Engineer)

Advanced AI/ML knowledge (Experience with ML frameworks – TensorFlow, PyTorch, Hugging Face; Knowledge of model training and evaluation; Advanced NLP techniques; Experience with multi‑agent systems or advanced RAG patterns)

MLOps knowledge: Model deployment, versioning, monitoring, A/B testing

Azure AI services: Document Intelligence, Cognitive Search, Azure AI Studio, Azure Machine Learning

Search technologies: Azure Search, Sinequa, Elasticsearch, Lucene‑based systems

Advanced Spark optimisation and performance tuning

Real‑time data processing and streaming architectures (Kafka, Azure Event Hubs)

Pharmaceutical, healthcare, or regulated industry experience

Experience with compliance requirements: HIPAA, GxP, 21 CFR Part 11

Experience with data visualisation libraries (D3.js, Plotly, Chart.js)

Software security best practices and secure coding

FinOps practices: Cloud cost optimisation and management

Experience mentoring junior engineers

Closing Date for Applications: Friday 30th January 2026 (COB)

Equal Opportunity Statement
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

Adjustments to the Process
We encourage you to explore with our hiring team what the opportunities are for flexibility. If you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at UKRecruitment.Adjustments@gsk.com. If your enquiry does not relate to adjustments we will not be able to support you through these channels. For further FAQs, see the Recruitment guide.

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