Python Developer
This is a remote position.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
- 3 years of professional experience in backend development using Python.
- Strong hands-on experience with Python frameworks such as Django, FastAPI, or Flask.
- Solid experience designing and developing RESTful and/or GraphQL APIs.
- Strong working knowledge of PostgreSQL and at least one NoSQL database (e.g., MongoDB).
- Experience with ORM frameworks (Django ORM, SQLAlchemy) and writing optimized raw SQL queries.
- Practical experience with asynchronous processing and event-driven systems (Celery, Kafka, RabbitMQ).
- Working knowledge of LLM integration and RAG systems, including vector databases and embedding workflows.
- Experience integrating third-party APIs with secure authentication and error handling.
- Familiarity with Docker, CI/CD pipelines, and production deployments.
- Experience with monitoring, logging, and performance optimization tools (Prometheus, ELK, Datadog).
Design and Develop Python-Based Backend Services
- Build scalable, maintainable backend applications using Python frameworks (Django, FastAPI, Flask).
- Develop RESTful or GraphQL APIs that enable seamless communication between frontend and backend services.
- Write clean, well-documented code following PEP 8 standards and best practices.
- Participate in code reviews and contribute to continuous improvement of code quality.
Build and Optimize Data Pipelines and Database Solutions
- Design and implement efficient database schemas using PostgreSQL and MongoDB.
- Develop data processing pipelines for regulatory intelligence and compliance analysis.
- Optimize database queries and implement caching strategies for improved performance.
- Work with ORM frameworks and raw SQL as needed.
- Maintain airflow DAGs for ETL processes and data workflows.
Develop and Maintain LLM Chat Agents and RAG Systems
- Design and implement conversational AI agents powered by Large Language Models (LLMs) for compliance queries and regulatory guidance.
- Build and maintain Retrieval-Augmented Generation (RAG) systems that combine LLMs with vector databases for accurate, context-aware responses.
- Integrate LLM APIs (OpenAI, Anthropic, open-source models) with backend services.
- Manage vector embeddings and ensure efficient retrieval from vector databases (Pinecone, Weaviate, Milvus, etc.).
- Monitor LLM accuracy, and cost optimization.
Develop Event-Driven and Asynchronous Systems
- Build event-driven microservices using message queuing systems (Kafka, RabbitMQ, Celery).
- Implement asynchronous task processing for long-running operations.
- Design systems that handle high-throughput data processing reliably.
Integrate Third-Party APIs and Services
- Integrate external services such as blockchain APIs, payment gateways, and data providers.
- Implement secure API authentication and error handling.
- Build robust integration layers that abstract external dependencies.
Monitor, Debug, and Optimize Performance
- Use monitoring and logging tools (Prometheus, ELK Stack, Datadog) to track application health.
- Identify and resolve performance bottlenecks at the code and database level.
- Contribute to incident response and troubleshooting of production issues.
- Monitor LLM latency, token usage, and system performance.
Collaborate and Mentor
- Work effectively with frontend developers, product managers, QA, and DevOps teams.
- Mentor junior developers and conduct code reviews.
- Participate in architectural discussions and technical planning.
- Contribute to documentation and knowledge sharing within the team.