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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading the design and delivery of AI products, focusing on architecture, API design, and integration standards while mentoring engineering teams. Proficient in modern frontend frameworks and cloud deployment, with a strong emphasis on production-scale AI orchestration and evaluation.
Highest-signal resume keywords
AI Product DeliveryFrontend ArchitectureAPI Design StandardsLLMOps StrategyCloud Deployment
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ScienceFull-Stack EngineeringAPI DevelopmentAI OrchestrationReactNext.jsPythonTypeScriptAWS
Soft Skills
MentoringCollaborationCommunication
Tools & Technologies
AzureGCPAgent FrameworksEvaluation PipelinesProduction Monitoring
Certifications & Qualifications
Bachelor's DegreeMaster's DegreePhD
Industry Keywords
Regulated IndustryLife Sciences
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformJavaScriptNext.jsPythonReactTypeScript
About the role
Key responsibilities & impact- Lead the design and delivery of a significant AI product area spanning modelling workflows and user-facing applications
- Own architecture, quality and outcomes across modelling workflows, platforms, APIs and interfaces
- Define standards and review patterns for work built by digital workers
- Design agentic research systems for experimentation, evaluation and product iteration
- Partner with product, design and research to shape product direction and communicate trade-offs
- Define API layers, integration contracts, non-functional requirements and API design standards
- Lead shared infrastructure and tooling that reduces integration cost across teams
- Design production-scale AI orchestration architectures, including agent frameworks, workflows, retrieval, tool use and guardrails
- Define standards for AI integration, evaluation and responsible deployment
- Resolve production AI failure modes
- Lead frontend architecture, UI patterns, component libraries and AI interface design
- Lead LLMOps and observability strategy, including evaluation pipelines and production monitoring
- Define model lifecycle, versioning and inference cost-tracking standards
- Set engineering standards and improve test coverage, API contract quality and deployment reliability
- Mentor junior and mid-level engineers through pairing, review and direct feedback
Requirements
What you’ll need- Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics or a related quantitative field, or equivalent practical experience
- 8+ years of combined experience across applied ML or data science and full-stack engineering
- Significant experience leading delivery of complex, user-facing AI products
- Expertise across modelling and evaluation, modern frontend frameworks, backend services and cloud deployment
- Experience with React or Next.js, Python or TypeScript, and AWS, Azure or GCP
- Experience leading API layers serving multiple consumers, including integration contracts and non-functional requirements
- Experience designing production-scale AI orchestration, including LLM integration, retrieval, tool and function calling, agent frameworks, evaluation, and cost, latency and quality trade-offs
- Experience leading frontend architecture and LLMOps, including evaluation pipelines, production monitoring and model lifecycle management
- Experience designing and operating agentic systems for continuous research or product iteration
- Experience establishing AI-assisted development patterns adopted by a team
- Master's or PhD preferred
- Technical leadership of AI products combining modelling and full-stack delivery preferred
- Experience building or improving internal developer or research tooling preferred
- Experience in a regulated industry, such as life sciences, preferred
Benefits
Comp & perks- Comprehensive benefits program for US employees (details provided in GSK US Benefits Summary)
- Flexible working options, including hybrid arrangements depending on team needs