Python Azure Solution Architect

Job description

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