Python Developer

We are looking for an experienced Python Developer to join a core engineering team and take part in building and scaling a high-load Geospatial AI data platform. This role focuses on bringing Data Science models into production and converting large volumes of raw imagery into structured, actionable insights that power a data-driven product. The position is well suited for engineers who enjoy solving complex problems at scale and working with big data systems.

Key Responsibilities

• Data Pipeline Development: Design, implement, and optimize reliable ETL pipelines for ingesting, cleaning, transforming, and loading large-scale geospatial datasets.
• API Development & Deployment: Develop, deploy, and maintain fast, scalable RESTful APIs using modern Python frameworks (such as FastAPI or AWS Lambda with Powertools).
• Model Integration & Productionization: Collaborate closely with Data Scientists to containerize, deploy, and maintain machine learning models (for example, roof age prediction) in a production environment.
• Code Quality & Performance Optimization: Write clean, maintainable, testable Python code. Continuously improve performance, latency, and scalability to support high request volumes.
• System Architecture: Participate in the design and implementation of microservices and serverless architectures with a strong focus on availability, security, scalability, and observability.
• Collaboration: Work in an Agile environment alongside Data Scientists, DevOps engineers, and Product Managers to turn business requirements into technical solutions.

Required Qualifications

• Bachelor’s degree in Computer Science or a related technical field.
• 4+ years of professional experience as a Python Developer, preferably on data-intensive backend systems.
• Strong expertise in Python 3 and adherence to PEP8 standards.
• Solid experience with OOP and SOLID principles.
• Proven experience designing and building production-grade APIs using modern Python frameworks (e.g. FastAPI or AWS Lambda with Powertools).
• Hands-on experience with AWS services such as S3, SQS, EC2, API Gateway, Lambda, DynamoDB, and infrastructure tools like CloudFormation or SAM, using boto3.
• Experience with Docker and Kubernetes.
• Strong Linux experience, preferably Ubuntu.
• Experience working with SQL databases (e.g. PostgreSQL).
• Proficiency with Git and collaborative development workflows.
• Good English communication skills.

Preferred / Bonus Qualifications

• Experience with geospatial libraries such as GeoPandas, GDAL, Shapely, or Rasterio.
• Familiarity with model serving solutions (e.g. NVIDIA Triton Inference Server).
• Experience with workflow orchestration tools like Apache Airflow.
• Experience working with on-premise servers.
• Knowledge of CI/CD pipelines (e.g. GitHub Actions) and general DevOps best practices.