Responsibilities
- Develop and maintain AI applications using Flask, Django, or FastAPI frameworks.
- Participate in the full software development lifecycle from requirements gathering to deployment.
- Deliver at least 2-3 projects as a developer using these frameworks, demonstrating proficiency and understanding of best practices.
- Demonstrate proficiency in core Python concepts including iterators, generators, object‑oriented programming (OOP), Python shell (REPL), and object‑relational mapping (ORM).
- Implement efficient data structures and handle exceptions effectively.
- Possess knowledge of contemporary Python libraries for LM orchestration such as LangChain, LlamaIndex, Autogen, and TaskWeaver, and utilize these libraries to handle complex scenarios and optimize AI applications effectively.
- Implement the AutoGen framework for agentic flows using Python.
- Implement GPTCache in the AI applications.
- Leverage DsPY framework for subtraction of prompt engineering as code.
- Build and deploy AI applications using cloud services provided by Azure or AWS.
- Configure and manage cloud infrastructure to ensure scalability, reliability, and performance of deployed applications.
- Stay updated with the latest trends and best practices in cloud computing.
Requirements
- 7‑10 years of overall technology experience in core application development.
- Expertise in Flask, Django, and FastAPI development with at least 2–3 projects delivered as a Python application developer.
- Strong core Python skills – iterators, generators, OOP concepts, Python shell (REPL), object‑relational mapping (ORM), data structures, and exception handling.
- Azure app services expertise for building and deploying AI applications using cloud services.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Engineering and Information Technology
Industries
IT Services and IT Consulting