Python Azure Solution Architect

We are looking for a hands-on Python 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