Are you passionate about building robust, scalable backend systems that support cutting-edge digital experiences? At MapsPeople, we’re looking for a Senior Python Developer (Senior Backend / Automation Engineer) to strengthen the infrastructure behind our indoor mapping platform. 

You’ll join a collaborative and skilled engineering team as we evolve our system into a cloud-native, event-driven architecture. This role will focus on developing APIs, building and maintaining data workflows in Airflow, and supporting automation efforts across our platform.

 If you have experience with geospatial tools like QGIS, that’s a big bonus! Our Engineering team is a creative group of problem-solving developers who thrive on technical challenges and believe in building future-proof solutions. We understand that the best platforms are built through extendable architecture, scalable infrastructure, and close collaboration between teams.

What you will do

• Take lead in designing, building, and maintaining workflow orchestration using Apache Airflow—driving reliability and transparency in data and ML pipelines.
• Collaborate closely with ML engineers and data teams to support the deployment and operationalization of machine learning models.
• Help define and improve our platform architecture, ensuring it remains secure, scalable, and maintainable with the software architect.
• Drive automation efforts across infrastructure, data ingestion, and deployment workflows to reduce manual overhead and improve consistency.
• Participate in code reviews, technical discussions, and mentoring to elevate engineering quality across the team.
• Contribute to improving our DevOps practices and cloud operations (GCP), including monitoring, alerting, and cost optimization.

We imagine you come with

• 10+ years of experience as a professional software engineer, with strong backend fundamentals.
• 5+ years of experience buildingdistributed backend systems, APIs, or automation workflows.
• Proficiency in Pythonand comfort working in data-heavy environments.
• Proficiency in Cloud-Native technologies such as Kubernetes and Open Telemetry
• Hands-on experience with Apache Airflowin a production setting.
• Experience with cloud platforms—preferably Google Cloud Platform (GCP)—including infrastructure-as-code, containerization (Docker), and CI/CD pipelines.
• A strong sense of system design, performance optimization, and clean architecture principles.
• Bonus: Familiarity with deploying or supporting machine learning models in production environments.
• Excellent communication skills, with the ability to work cross-functionally and occasionally represent technical perspectives in discussions with partners or customers.

What you get

In this role, you’ll be part of a highly skilled and supportive team working on a fast-evolving platform. You’ll gain opportunities to influence architectural decisions, own critical systems, and grow professionally—whether you’re deepening your backend expertise, expanding into ML ops, or mentoring future team members.

As benefits, we offer:

• A diverse, international work environment with engaging social events across teams and departments.
• A collaborative and dynamic workplace with a strong team spirit.
• Opportunities for professional growth
• Great office location in the North of Bucharest (Charles de Gaulle Plaza)
• Private healthcare subscription, food tickets
• Flexible working hours & hybrid way of working

Who we are:

MapsPeople is a world-leading provider of indoor mapping through our flagship product ‘MapsIndoors’. We connect people and buildings through dynamic indoor maps and real-time data visualizations, empowering occupants to make better decisions.

MapsIndoors powers a wide range of smart building technologies, including wayfinding, room and desk booking, occupancy, positioning, and much more.

We partner with large and innovative businesses that provide smart building solutions to help them increase their product value, grow their business, and reach our goal of mapping every smart building in the world - we’ve already mapped more than 25,000 of them.

Let's map the built world together!