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)