HIRING:

JOB TITLE: Large Language Models (LLM) Full Stack Engineer

WORK SET UP: On-site inC

Work Shift Schedule: Rotational

Develop and integrate applications with Large Language Models (LLMs) and other enterprise services. Leverage front-end and server-side technologies to develop APIs, implement DevOps practices, and optimize Artificial Intelligence (AI) applications.

Summary: As a LLM Full Stack Engineer, you will engage in the development and integration of applications utilizing Large Language Models and various enterprise services. Your typical day will involve collaborating with cross-functional teams to design and implement APIs, optimizing AI applications, and applying DevOps practices to enhance the efficiency and performance of the systems you work on.

Skills and Qualifications Required:

Professional & Technical Skills:

• Required Skill: Expert proficiency in Generative AI.

• Additional Good To Have Skills: Experience with Java Enterprise Edition, Python (Programming Language), DevOps.

• Strong understanding of machine learning principles and algorithms.

• Experience in developing and deploying scalable applications in cloud environments.

• Proficiency in API design and development, ensuring robust and secure integrations.

• Familiarity with front-end technologies and frameworks to create user-friendly interfaces.

Additional Information:

• The candidate should have a minimum 3 years of experience in Generative AI.

• This position is based at our Cebu office.

• Minimum 3 years of relevant experience is required

Roles & Responsibilities:

• Expected to be an SME.

• Collaborate and manage the team to perform.

• Responsible for team decisions.

• Engage with multiple teams and contribute on key decisions.

• Provide solutions to problems for their immediate team and across multiple teams.

• Facilitate knowledge sharing and mentorship within the team to foster a culture of continuous learning.

• Analyze project requirements and translate them into technical specifications to guide development efforts

• Monitor and evaluate the performance of applications, making recommendations for improvements.