Back- End Developer

at  GenderGP

POSITION OVERVIEW:

We are seeking a highly skilled Software Developer with a strong background in Generative AI (GenAI) development. The ideal candidate will have a proven track record in developing robust backend systems and integrating third-party solutions. This role requires proficiency in Python, API development, GitHub, Docker, and Azure AI/ML Studio. A solid understanding of Object-Oriented Programming (OOP) and software quality assurance is essential. Experience in data engineering and analytics is also desired. You will collaborate closely with our frontend developers, product owners, and data engineers to create engaging, high-performance applications.
A talented and motivated Backend Developer with a strong background in Machine Learning (ML) and Artificial Intelligence (AI) to join our innovative team.

EDUCATION:

• Degree in Computer Science, Statistics, AI, Data Science, Data Analytics, IT, or a related field is mandatory.

EXPERIENCE:

• Proven experience in backend development with a focus on GenAI, LLM chatbots, and third-party integrations.
• Strong knowledge in Object-Oriented Programming and System Design Principles.
• Experience with Prompt Engineering, Retrieval-Augmented Generation (RAG) pipelines, and model fine-tuning.
• Proficient in Python and API development.
• Demonstrated experience in shipping production-ready frontends, including performance optimization and ensuring high standards of quality.
• Understanding of RESTful APIs and experience in API integration.
• Strong experience with GitHub for version control.
• Proficiency with Docker for containerization and managing applications within Docker environments.
• Server-side debugging experience, including logging, audit trails, and application monitoring.
• Basic knowledge of data engineering and analytics.

SKILLS:

• Experience working within budget constraints on cloud platforms like Azure or AWS.
• Knowledge of additional programming languages such as Java or C#.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork skills.
• Ability to work independently and as part of a team in a fast-paced environment.
• Familiarity with Agile/Scrum methodologies.

• Backend Development: Design, develop, and maintain backend services and systems to ensure high performance and responsiveness.
• GenAI Integration: Develop and integrate Generative AI and Large Language Model (LLM)-based chatbots into various platforms to enhance user experience and interaction.
• GenAI: Leverage Azure AI/ML Studio for developing, training, and deploying generative AI models.
• Third-Party Integration: Work with third-party providers to seamlessly integrate their solutions with our systems.
• API Development: Design and implement robust APIs in Flask, FastAPI or DotNet to support various applications and services.
• Security: Implement and manage authentication and authorization mechanisms to ensure secure access and data privacy.
• Performance Optimization: Identify bottlenecks and optimize applications for maximum speed and scalability.
• Production-Ready Systems: Ship production-ready backends, including code optimization and thorough testing to ensure stability and performance.
• Collaboration: Work closely with frontend developers, AI engineers, data engineers, and product managers to deliver high-quality solutions.
• Version Control: Utilize GitHub for version control to ensure smooth collaboration and code management.
• Code Quality: Write clean, maintainable code, perform code reviews, and adhere to best practices in version control, testing, and continuous integration.
• Containerization: Use Docker to containerize applications for consistent and efficient deployment.
• Documentation: Create documentation and specifications for developers to follow during implementation.
• OOP Principles: Apply object-oriented programming principles to design and implement scalable and maintainable code.
• Software Quality Assurance: Ensure the quality and reliability of software through rigorous testing.
• System Design: Apply knowledge of system design principles and industry best practices.
• Data Management: Work with databases (SQL and NoSQL) to design efficient data storage solutions that support ML workflows.