Sr Python Backend Engineer

Hand on Python engineer who loves building scalable applications and robust RESTful APIs
Responsibilities
Translate complex business requirements into detailed technical specifications, architectural designs, and API contracts.
Create and implement microservice architectures via APIs and services, ensuring seamless integration and data flow
Develop and integrate advanced Generative AI models and Agentic AI approaches into new and existing applications.
Optimize application code and architecture for performance, scalability, security, and cost-effectiveness.
Work with data scientists to integrate Agents into application endpoints and user interfaces (fastAPI, uvicorn)
Collaborate effectively with cross-functional teams, including product managers, data scientists, designers, and DevOps engineers, to deliver features iteratively.
Qualifications
5+ years of experience in software development, with significant experience in cloud-based application development and API design.
Strong software engineering background, including developing applications, RESTful APIs, and integrating front-end technologies (if applicable to the role).
Proficiency in modern programming languages (e.g., Python).
Understanding of machine learning lifecycle, MLOps principles, and responsible AI/ML practices from an application integration perspective.
Experience with database technologies (SQL/NoSQL) and data integration patterns.
Familiarity with cloud services relevant to application development (e.g., Azure Webapps, Azure Functions, Azure API Management, Azure Cosmos DB, Azure Databricks, Azure ML services for model consumption).
Good experience in configuring and managing CI/CD pipelines (e.g., Azure DevOps Pipelines, GitHub Actions) for complex application landscapes, including monorepos and multi-application deployments.
Basic proficiency in scripting languages (e.g., PowerShell, Bash) for automating operational tasks, deployments, and creating standardized project templates ('cookie-cutter' style automation).
Good understanding of containerization technologies (e.g., Docker, Kubernetes).
Experience with monitoring and logging tools to manage application and infrastructure health (e.g., Azure Monitoring, Azure AppInsights)