GSK
Senior, Full Stack Engineer
USA - Pennsylvania - Philadelphia +1 · Hybrid (Remote & On-site) · Senior · Full-time · Posted Oct 26, 2026
- Location
- USA - Pennsylvania - Philadelphia
Durham Blackwell Street - Experience
- 8+ years of combined experience across applied ML or data science and full-stack engineering.
- Education
- Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience.
About the job
Leads the design and delivery of a significant AI product area, spanning modelling workflows and user-facing applications, and establishes engineering standards and agentic systems for ongoing research and product iteration.
What you'll do
- Set technical direction and architecture across modelling pipelines, APIs, AI integration, frontend, and LLMOps.
- Design production agentic research and AI orchestration systems, including evaluation, monitoring, and responsible deployment.
- Set engineering and agent-generated work standards, partner with product, design, and research, and mentor junior and mid-level engineers.
What they ask for
- Bachelor's degree in a related quantitative field, or equivalent practical experience.
- 8+ years of combined experience across applied ML or data science and full-stack engineering, including significant time leading delivery of complex, user-facing AI products.
- Expertise across modelling and evaluation, frontend frameworks, backend services, and cloud deployment.
- Experience leading multi-consumer API design, production-scale AI orchestration, frontend architecture and LLMOps, and agentic systems and AI-assisted development patterns adopted by a team.
Nice to have
- Master's or PhD in a related quantitative field, or equivalent practical experience.
- Experience leading AI products from build through scale, creating AI developer or research tooling, or working in a regulated industry.
Tools
React, Next.js, Python, TypeScript, AWS, Azure, GCP
AI focus
Builds and leads AI products and agents, including agentic research and product-iteration systems, production AI orchestration, evaluation, retrieval, tool use, LLMOps, and responsible deployment.
Model-written summary · the original posting is authoritative