Python Developer

Role Summary

1. Demonstrate solid proficiency in Python development, writing clean, maintainable code.  

2. Collaborator in the design and implementation of AI-driven applications leveraging large language models (LLMs).  

3. Develop and maintain Django-based RESTful APIs to support backend services.  

4. Integrate with LLM provider APIs (e.g., GPT, Claude, Cohere) and agent frameworks (LangChain, AgentStudio).  

5. Build and optimize data pipelines for model training and inference using Pandas, NumPy, and Scikit-learn.  

6. Ensure robust unit and integration testing via pytest to maintain high code quality.  

7. Participate in agile ceremonies, contributing estimations, design discussions, and retrospectives.  

8. Troubleshoot, debug, and optimize performance in multi-threaded and distributed environments.  

9. Document code, APIs, and data workflows in accordance with software development best practices.  

10. Continuously learn and apply new AI/ML tools, frameworks, and cloud services.  

Key Responsibilities

1. Write, review, and optimize Python code for backend services and data science workflows.  

2. Design and implement Django REST APIs, ensuring scalability and security.  

3. Integrate LLMs into applications: handle prompt construction, API calls, and result processing.  

4. Leverage agent frameworks (LangChain, AgentStudio) to orchestrate complex LLM workflows.  

5. Develop and maintain pytest suites covering unit, integration, and end-to-end tests.  

6. Build ETL pipelines to preprocess data for model training and feature engineering.  

7. Work with relational databases (PostgreSQL) and vector stores (FAISS, Weaviate, Milvus).  

8. Containerize applications using Docker and deploy on Kubernetes or serverless platforms (AWS, GCP, Azure).  

9. Monitor and troubleshoot application performance, logging, and error handling.  

10. Collaborate with data scientists to deploy and serve ML models via FastAPI or vLLM.  

11. Maintain CI/CD pipelines for automated testing and deployment.  

12. Engage in technical learning sessions and share best practices across the team.  

Desired Skills & Qualifications

- 1–3 years of hands-on experience in Python application development.  

- Proven pytest expertise, with a focus on test-driven development.  

- Practical knowledge of Django (or FastAPI) for building RESTful services.  

- Experience with LLM APIs (OpenAI, Anthropic, Cohere) and prompt engineering.  

- Familiarity with at least one agent framework (LangChain, AgentStudio).  

- Working experience in data science libraries: NumPy, Pandas, Scikit-learn.  

- Exposure to ML model serving tools (MLflow, FastAPI, vLLM).  

- Experience with container orchestration (Docker, Kubernetes, Docker Swarm).  

- Basic understanding of cloud platforms (AWS, Azure, or GCP).  

- Knowledge of SQL and database design; familiarity with vector databases.  

- Eagerness to learn emerging AI/ML technologies and frameworks.  

- Excellent problem-solving, debugging, and communication skills.  

Education & Attitude

- Bachelor’s or Master’s in Computer Science, Data Science, Statistics, Mathematics, or related field.  

- Growth-mindset learner: proactive in upskilling and sharing knowledge.  

- Strong collaboration ethos and adaptability in a fast-paced AI environment.