Staff, Full Stack Engineer

GSK; Philadelphia (Philadelphia County); Hybrid; USD 180,000 - 230,000; Full time

Job summary

GSK in the United States (hybrid) is seeking a Staff Full Stack Engineer to lead the technical direction for the AI product stack across EAI, spanning modelling workflows, platforms, APIs and interfaces.

The role focuses on integration and orchestration architecture, agent-driven development, and defining standards for scalable AI capabilities while ensuring production quality and governance.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience.
• 10+ years of experience in applied ML (ML) or data science and full-stack engineering, incl. modelling pipelines, evaluations, platforms and APIs.

Responsibilities

• Set multi-quarter technical direction for the AI product stack across EAI and lead end-to-end bets with durable impact.
• Define agentic research practice for continuous experimentation and auto-research, evolving production models.
• Set operating model for agent-generated engineering work including governance, evaluation gates, and incident handling.

Skills

AI Platforms

Change Management

Data Analysis

Machine Learning

Model Evaluation

Performance Analysis

Product Delivery

Product Design

Product Lifecycle Management

Product Roadmapping

Roadmap Development

Statistical Analysis

User Needs Analysis

Machine Learning Model Management

Job description

Enterprise AI (EAI) builds AI products that combine real modelling work with user-facing applications, and ships them to production. Full Stack Engineers move across data, models, platforms, APIs and interfaces in a single workflow. In our operating model, digital workers do much of the hands-on build. They generate services, APIs, interface components and tests, run evaluations and monitor what is in production. Our engineers set the architecture and standards that work is built to, and own the quality of what ships. EAI products and agents draw on a governed context layer that makes data, meaning, permissions and history retrievable at the moment they are needed. Full Stack Engineers build the products and agents that consume it, and decide how that context reaches users. The Staff Full Stack Engineer sets technical direction for the AI product stack across EAI. The role is accountable for the integration and orchestration architecture through which EAI products and agents draw on the governed context layer, and is EAI's internal authority on how AI capabilities reach users. Sets multi-quarter technical direction for the AI product stack across EAI: modelling workflows, platforms and APIs, AI-powered interfaces and the agentic systems that connect them. Owns the integration and orchestration architecture through which EAI products and agents draw on the governed context layer, and defines the standards engineers and digital workers build to. Defines EAI's agentic research and development practice for continuous experimentation, auto-research and agent-driven application development, and develops the senior engineers who carry it forward.

Key Responsibilities

Technical Strategy & Research Practice Set multi-quarter technical direction for the AI product stack across EAI, and lead the most ambitious end-to-end bets, turning vague, high-stakes problems into shipped systems with durable impact.

Define EAI's agentic research practice for continuous experimentation and auto-research, evolving production models, and using agents to drive research and application iteration.

Agent-Operated Engineering Set the operating model for agent-generated engineering work: what digital workers build and change on their own, what requires human approval, which evaluation gates their work must pass and how incidents escal…

Why You?

Basic Qualifications

Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience. 10+ years of experience in applied machine learning (ML) or data science and full-stack engineering, including experience building and operating user-facing AI products. Experience across the AI product stack, including modelling pipelines, evaluations, platforms and APIs, modern web frameworks, and data and cloud infrastructure. Experience designing and operating production AI products, including large language model (LLM) selection and integration, orchestration and tool-use architectures, retrieval and context integration using protocols such as Model Context Protocol (MCP), safety, and cost, latency and quality optimisation. Experience defining API, platform and frontend engineering standards for multiple teams, including interfaces designed for non-deterministic, agent-driven behaviour. Experience building large language model operations (LLMOps), evaluation and monitoring infrastructure for production AI systems. Experience defining and scaling agentic research and product workflows, such as auto-research, continuous evaluation and agent-driven application development. Experience setting multi-quarter technical strategy across multiple engineering teams.

Preferred Qualifications

Master's or PhD strongly preferred, in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience. Prior Staff, or equivalent, experience at an organisation shipping non-trivial AI products that combine modelling and full-stack delivery. Defined organisation-wide engineering strategy, particularly for agentic research and product workflows, and seen it through to measurable outcomes. Experience in a regulated industry, such as life sciences, where data integrity and auditability are mandatory. Public technical contributions, such as talks, writing or open source, on AI-native, agent-augmented engineering Experience defining API and platform architecture standards for multiple engineering teams and making platform decisions to improve reliability and developer productivity. Experience with AI integration architecture, including large language model (LLM) selection, orchestration patterns and LLM operations (LLMOps)and implementing evaluation pipelines and AI observability practices across multiple teams. Experience defining frontend engineering standards for AI products and designing non-deterministic, agent-driven user interfaces. Experience defining LLMOps standards, including AI system observability, evaluation and governance and building evaluation and monitoring infrastructure for production AI systems. Experience defining full-stack engineering standards, including standards for agent-generated code. Experience developing developer tooling and shared component strategies.

What Success Looks Like

In the first 12 months, the person in this role will have: Set and begun executing a multi-quarter technical strategy for the AI product stack across EAI. Established the operating model and standards under which engineers and digital workers build across platforms, APIs and interfaces, and led at least one platform investment that changed how teams build. Defined the integration and orchestration architecture through which EAI products and agents draw on the governed context layer, with evaluation and observability standards in production. Defined EAI's approach to agentic research and AI-assisted development, with measurable adoption and impact on velocity and quality. Raised the architectural independence of EAI's senior engineers through standards and coaching.

Work Arrangement

This role is hybrid and based in the United States. You will spend scheduled time on-site to collaborate and engage with your team. Fully remote arrangements are not available.

Skills

AI Platforms, Change Management, Data Analysis, Feature Prioritization, Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis

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.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, 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.