Python Azure Solution Architect

We are looking for a hands-onPython Azure Solution Architect to join a greenfield Modeling-as-a-Service (MaaS) platform initiative. The platform is being developed on Microsoft Azure to provide a standardized approach to the development, validation, deployment, and monitoring of financial models.

In this role, you will combine technical leadership, backend engineering, and team management. You will guide a team of 5+ engineers and take ownership of the design and implementation of scalable backend services used to deploy and interact with different types of financial models.

Responsibilities

• Drive the technical design and development of backend components for the MaaS platform within a secure Azure environment
• Design and develop RESTful APIs for deploying, managing, and querying financial models
• Develop scalable backend solutions using Python, FastAPI, and Pydantic
• Use Azure Databricks and MLflow-based approaches to support model deployment and serving
• Define technical standards for model packaging, deployment workflows, MLflow integration, and API interfaces
• Establish development practices that ensure high standards of code quality, testing, reliability, and maintainability
• Build and improve CI/CD pipelines with GitLab, supporting automated testing and deployments
• Provide technical direction, mentorship, and guidance to a team of 5+ engineers
• Work closely with architects, engineering teams, and business stakeholders to shape technical solutions and deliver platform capabilities
• Contribute to an Agile engineering culture and continuously improve development and delivery processes

Requirements

• 8+ years of experience in software or data engineering, with at least 2 years of experience in a technical leadership position
• Strong hands-on expertise in Python, including Python Core, asynchronous programming, multithreading, exception handling, and REST API development
• Solid experience with FastAPI and Pydantic
• Strong understanding of backend architecture, distributed systems, and API design
• Proven experience with Microsoft Azure, particularly Azure Databricks, Azure App Service, and IAM/RBAC
• Experience with MLflow or comparable tools and frameworks for model lifecycle management and deployment
• Good knowledge of GitLab, CI/CD pipelines, and DevOps practices
• Hands-on experience with Docker and Kubernetes
• Strong analytical and problem-solving skills, with the ability to make sound technical decisions
• Excellent communication, leadership, and stakeholder-management skills
• Experience working in Agile, cross-functional engineering teams
• English proficiency at B2 level or higher

Nice to have

• Background in financial modeling, machine learning platforms, or model-serving solutions
• Experience building Modeling-as-a-Service, Machine Learning-as-a-Service, or similar platforms
• Understanding of ML model deployment, monitoring, and lifecycle management
• Experience working with enterprise platforms operating under strict security, access-control, and compliance requirements