Lead Software Engineer – AI Product Development (Data) at Clarivate Analytics – Barcelona | Jobyssey

Overview

In this Lead role, you shape AI-powered product platforms, building reliable backend services and data pipelines. You’ll work within the LS&H Innovation group to drive AI-enabled capabilities, collaborating across engineering, product, and cloud ops to deliver scalable solutions. You’ll tackle reliability challenges in LLM-driven applications and guide technical direction from concept to production. This opportunity combines hands-on backend work with strategic influence in a fast-paced, cross-functional team.

Compensaciones / Beneficios

hybrid work
flexible hours
equal employment opportunities
core business hours in CET
global time-zone availability
focus on AI innovation

Responsabilidades

Define and steer AI platform initiatives from concept to production
Design, develop, and maintain backend services (APIs, microservices, ETL) in Azure or AWS
Translate requirements into high-quality code and proofs-of-concept
Collaborate with Cloud Operations, Solution Architecture, Product Engineering, and SMEs
Build and iterate LLM-based or agentic AI applications with attention to reliability and AI limitations
Evaluate and integrate with multi-language applications (e.g., Java, Typescript) when needed
Lead technical approach from design through implementation with ownership
Test and improve solutions via unit tests, automation, and iterative development
Advance projects from concept to prototype and contribute to production-focused plans
Operate in an agile, fast-paced environment and drive continuous improvement

Requisitos principales

7+ years of professional software engineering experience
4+ years developing backend systems in Python (APIs, microservices, ETL pipelines)
5+ years of experience in cross-functional, agile teams
3+ years of experience with LLMs or agentic AI applications
Bachelor’s degree in computer science, Software Engineering, or related field (or equivalent)
Experience with cloud environments (Azure or AWS) and deploying backend services

collaboration in cross-functional teams
mentoring or technical guidance to peers
initiative and ownership
Python backend engineering
APIs and microservices
ETL pipelines and data engineering

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