Lead Software Engineer - AI Product development - Clarivate Analytics

In this role you will lead the development of AI-powered backend systems, building reliable, scalable solutions in a small, skilled team. You will shape architecture and deliver APIs, microservices, and ETL pipelines in cloud environments. You’ll drive AI-driven product initiatives, collaborating across engineering, product, and cloud operations to scale LS&H capabilities. This is a hands-on leadership position with a strong impact on reliability and product direction in a fast-paced setting.

• hybrid work model (office 2-3 days a week)
• full-time role
• CET core hours with global flexibility
• collaborative team
• opportunity to shape AI platform direction

• Scope and shape AI platform initiatives for LS&H products from concept to implementation
• Design, develop, and maintain backend services (APIs, microservices, ETL) in Azure/AWS
• Translate needs from multiple teams into high-quality, reliable code and proof-of-concepts
• Collaborate with Cloud Operations, Solution Architecture, Product Engineering, and SMEs
• Build and iterate LLM-based or agentic AI applications, ensuring reliability and quality
• Evaluate integration with applications in other languages (e.g., Java, Typescript)
• Lead the technical approach from design through implementation
• Test and improve solutions via unit tests, automation, and iterative development
• Advance projects from concept to prototype and contribute to production roadmaps
• Work in an agile environment and contribute to continuous improvement culture

• Bachelor’s degree in computer science, software engineering, or related field, or equivalent experience
• At least 7 years of professional software engineering experience
• At least 4 years backend experience in Python (APIs, microservices, ETL pipelines)
• At least 5 years collaborating in cross-functional, agile teams
• At least 3 years working with LLMs or agentic AI applications with awareness of reliability challenges
• Experience contributing to or defining software architecture for complex systems
• Experience with AI/ML workflows (e.g., RAG, vector databases, evaluation techniques)
• Experience in cloud environments (Azure or AWS), including deploying or integrating backend services
• Mentoring or providing technical guidance to other engineers (preferred)

• collaborative
• mentoring
• strong communication
• Python backend engineering
• Azure / AWS
• LLM-based or agentic AI development