Purpose of Onyx

The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.

Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML, GenAI, and analysis platforms, all geared toward:

• Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”.

• Providing best-in-class AI/ML, GenAI, and data analysis environments to accelerate our predictive capabilities and attract top-tier talent.

• Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time.

At GSK we see a world in which advanced applications of AI and GenAI will allow us to develop transformational medicines using the power of genetics, functional genomics, and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more, feel better, and live longer. It is an ambitious vision that will require the development of products at the cutting edge of AI and Machine Learning. We're looking for a highly skilled Senior GenAI Platform Engineer to help us make this vision a reality.

Our GenAI Engineering team is focused on developing first-in-class GenAI capabilities at scale, including complex agent architectures, LLM training, optimized LLM deployments and end-to-end production-grade multi-agent applications that impact all R&D teams at GSK.

The GenAI team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career from day one, supporting individuals in dedicating 20% of their time towards personal development.

Key Responsibilities:

• Serve as a key engineer for the GenAI platform and contribute technical expertise to teams in closely aligned technical areas such as AIML Platform, DevOps, Compute and Cloud.

• Co-design major software components of the GenAI Platform and contribute to development of production code in Python and participate in both design reviews and PR reviews.

• Accountable for key component(s) of GenAI Platform with particular focus on usability, reproducibility and performance at scale

• Integrate with DataOps, and Data Engineering products for best performance and ease of use in ML training at scale

• Participate in scrum teams and contribute technical expertise to teams in closely aligned technical areas.

• Able to design innovative strategies and ways of working to create a better environment for the end users

• Standard bearers for proper ways of working and engineering discipline, including CI/CD best practices and proactively contribute to improvements within your engineering area.

Why You?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• Bachelor’s, Master’s or PhD degree in Computer Science, Software Engineering, or related discipline.

• 4+ years of software engineering experience building production systems

• Experience with Python proficiency in writing well instrumented, tested, and maintainable code

• API design and developer experience focus (versioning, SDKs, docs) and ability to collaborate with ML/security/product teams

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

• Experience building platform for service-specific (e.g. Models, Agents, MCP services) lifecycle management involving development tools, CI/CD workflows, as well as API discovery, routing, authentication, observability

• Deep knowledge of integrating applications with LLMs and experience with an agent framework such as LangGraph

• Experience in operating production multi-tenant Vector DBs (e.g. Weaviate) and expertise with embedding/modeling best practices

• Experience with fine-tuning and/or optimized deployments of LLMs

• Experience with infrastructure-as-code and CI/CD tools (e.g. Terraform and Github Actions respectively)

• Google Cloud expertise, including and scalable cloud compute services, such as Google Batch and Vertex AI

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