Python Software Engineer - Temporary to Perm

About the role

The Python Software Engineer will design and develop robust, cloud-native systems that power intelligent automation and decision-making. This role involves building APIs, Azure Functions, and event-driven services that form the backbone of scalable, AI-ready enterprise applications.

Responsibilities

• Write clean, maintainable, and testable code in Python
• Design, build, and optimize APIs and Azure Function Apps to deliver performant, reliable, and secure cloud services
• Integrate with databases (SQL, NoSQL, or cloud-native data stores) and design effective data access patterns
• Implement event-driven architectures leveraging Azure Event Grid, Durable Functions, and API Management
• Rapidly prototype and experiment with new SDKs, APIs, and frameworks to support AI-driven and agentic workflows
• Develop monitoring, observability, and diagnostic tools to ensure reliability and performance
• Apply software engineering best practices, including automated testing, CI/CD, and cloud cost optimization
• Collaborate with peers through code reviews, technical design discussions, and mentorship

Qualifications

• 7–10+ years of professional software development experience in backend or full-stack engineering
• Proven ability as a hands-on problem solver who can translate complex requirements into reliable, maintainable solutions
• Proficiency in Python, with strong knowledge of object-oriented and functional programming principles
• Hands-on experience developing and deploying Azure Functions, APIs, and event-driven systems
• Experience integrating with databases and designing data interaction layers for performance and scalability
• Solid understanding of microservices, serverless architectures, and distributed systems
• Familiarity with Azure SDKs, Azure Cognitive Services, and cloud security best practices
• Strong communication and collaboration skills; thrives in agile, iterative development environments
• Practical exposure to AI/ML technologies, including LLMs, RAG, and orchestration tools like LangChain, AutoGen, or Semantic Kernel