What you'll do

Own core systems and their architecture, the production environment, and the platform's reliability, scalability, and performance—consistently delivering high-quality features
Drive optimization of resource usage and cost, using monitoring and load-testing data to guide engineering decisions across the team
Work closely with machine learning engineers and backend developers to bridge the gap between AI models and production-ready software
Drive discussions with multiple stakeholders and lead cross-team technical alignment and delivery

What we’re looking for

Several years building and operating Python backend services in production, with deep Python fundamentals and strong experience building APIs (FastAPI or similar)
A proven track record designing, owning, and scaling resilient distributed systems — including event-driven pipelines with messaging/task-queue systems (Kafka, RabbitMQ, Celery, etc.), performance optimization, and load testing at scale
Hands-on experience with cloud platforms (Azure, GCP, or AWS) and containerization (Docker, Kubernetes)
Experience integrating or operating LLMs or other ML models in production
Strong experience with observability (logging, metrics, dashboards) and debugging complex production issues
Ability to take end-to-end ownership of Python development, drive stakeholder discussions, and align delivery across teams
Strong problem-solving skills, genuine curiosity about how systems behave in production, and good written and spoken English
Experience working in an ISO 27001 / GDPR-compliant environment is a plus

Responsibilities

Own core systems and their architecture, the production environment, and the platform's reliability, scalability, and performance—consistently delivering high-quality features
Drive optimization of resource usage and cost, using monitoring and load-testing data to guide engineering decisions across the team
Work closely with machine learning engineers and backend developers to bridge the gap between AI models and production-ready software
Drive discussions with multiple stakeholders and lead cross-team technical alignment and delivery

Several years building and operating Python backend services in production, with deep Python fundamentals and strong experience building APIs (FastAPI or similar)
A proven track record designing, owning, and scaling resilient distributed systems — including event-driven pipelines with messaging/task-queue systems (Kafka, RabbitMQ, Celery, etc.), performance optimization, and load testing at scale
Hands-on experience with cloud platforms (Azure, GCP, or AWS) and containerization (Docker, Kubernetes)
Experience integrating or operating LLMs or other ML models in production
Strong experience with observability (logging, metrics, dashboards) and debugging complex production issues
Ability to take end-to-end ownership of Python development, drive stakeholder discussions, and align delivery across teams
Strong problem-solving skills, genuine curiosity about how systems behave in production, and good written and spoken English
Experience working in an ISO 27001 / GDPR-compliant environment is a plus