Senior Principal Software Engineer - R&D Tech

Job description Site Name: UK London New Oxford Street, USA - Pennsylvania - Upper Providence Posted Date: Jan 16 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. We're seeking a Senior Principal Software Engineer with broad expertise across software development, data engineering, cloud architecture, and AI/ML technologies. This is a hands‑on technical role where you'll spend the majority of your time writing code, building data pipelines, architecting cloud‑native solutions, and integrating AI/ML capabilities into production applications. You'll be a versatile engineer who can work across the full stack, understand data flows, leverage cloud services effectively, and apply AI/ML techniques to solve real‑world problems. 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 modern frameworks Cloud services experience, preferably Azure (App Services, Functions, Storage, or equivalent cloud services) 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 frameworks 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) Understanding of model training and evaluation Knowledge of NLP techniques beyond basic text processing 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) Please take a copy of the Job Description, as this will not be available post closure of the advert. When applying for this role, please use the 'cover letter' of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application. During the course of your application, you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process. If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements, please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process. #LI‑GSK #LI‑Hybrid 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 ...