Lead Software Engineer – AI Product Development (Data)

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