Ai Engineer

Responsibilities:

• Collaborate with the development team to design, develop, and maintain Python packages that meet the project requirements.
• Develop responsive and visually appealing user interfaces using HTML, CSS, and JavaScript frameworks such as React, Angular, or Vue.js.
• Build and maintain robust, scalable server-side applications using Node.js, Python, Ruby, Java, or other relevant languages.
• Develop and manage databases, ensuring high performance and responsiveness to front-end requests.
• Integrate in-house, open-source, and/or commercial LLMs into our software applications to enhance natural language processing capabilities.
• Utilize the Langchain framework to develop and deploy secure and scalable LLM applications.
• Design and implement APIs for seamless integration with other systems.
• Conduct code reviews and provide constructive feedback to team members.
• Troubleshoot and debug software issues, identifying and implementing effective solutions.
• Collaborate with cross-functional teams, including designers, product managers, and QA engineers, to deliver high quality software products.
• Stay updated with the latest industry trends and technologies to ensure the adoption of best practices.
• Participate in Agile development processes, including sprint planning, daily stand-ups, and retrospectives.

Requirements:

• Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
• Minimum of 3-5 years of professional experience in full-stack development.
• Proven experience with React for front-end frameworks
• Proven experience in developing Python packages, with a strong understanding of object-oriented programming principles.
• Strong proficiency in back-end languages (Node.js, Python).
• Experience with database management systems (SQL, NoSQL).
• Proficiency in HTML, CSS, and JavaScript.
• Preferred experience in chatbot AI, including ChatGPT, Copilot, Gemini and etc.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with LLMs and experience in integrating them into software applications. Hobby projects may also serve as evidence for this. 
• Strong knowledge of back-end frameworks, such as FastAPI
• Experience with testing frameworks and methodologies such as TestClient, Jest
• Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.
• Growth mindset: Demonstrate a growth mindset to understand clients' business processes and challenges.