Artificial Intelligence (AI) Technical Lead

PT Dian Swastatika Sentosa Tbk or its subsidiaries are looking for high potential candidates to be employed as an Artificial Intelligence (AI) Technical Lead. This role will focus on designing, developing, implementing, and maintaining AI/ML solutions, including Generative AI and LLM-based applications. The role will also provide technical leadership in AI initiatives and collaborate with AI Leads, IT teams, data teams, and business stakeholders to deliver AI solutions and drive the practical adoption of AI technologies across the organization.

Requirements:

1. Bachelor's degree in Computer Science, Information Technology, AI, Data Science, or related fields with a minimum GPA of 3.5 from a reputable university. Master’s degree is an advantage.

2. Minimum 3 years of experience in AI/ML, Software Engineering, Data Science, or a related technical field.

3. Strong programming skills, particularly in Python.

4. In depth understanding of Machine Learning, Deep Learning, Generative AI, LLM, NLP, and AI application development.

5. Experience with AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent.

6. Experience with LLM APIs, RAG, vector databases, prompt engineering, and AI agents is a plus.

7. Strong analytical and problem-solving skills.

8. Ability to work collaboratively in a cross-functional and fast-paced environment.

Responsibilities:

1. Design, develop, and implement AI/ML solutions based on business and technical requirements.

2. Develop and deploy Generative AI, LLM, NLP, and Machine Learning applications.

3. Build AI applications, models, APIs, and integrations with existing enterprise systems and data platforms.

4. Develop Proof of Concepts (PoCs) and convert successful AI use cases into production-ready solutions.

5. Perform data preparation, model development, testing, evaluation, and optimization.

6. Integrate AI models with applications, databases, APIs, and cloud platforms.

7. Implement and maintain RAG (Retrieval-Augmented Generation), AI agents, chatbots, and other LLM-based solutions where applicable.

8. Monitor AI model performance and troubleshoot technical issues in production.

9. Apply best practices for AI security, data privacy, scalability, and reliability.

10. Stay updated on emerging AI technologies, frameworks, and tools and assess their potential application.

11. Collaborate with AI Lead, Data Scientists, Software Engineers, IT teams, and business stakeholders to deliver AI initiatives.

12. Prepare technical documentation, architecture designs, and implementation guidelines.