Role: AI Product Engineer
Location: Jakarta (Relocation support provided by the organization)
YOE: 1 to 7 years
Must-Have Skills:
- Hands-on experience with Deployment
- Expertise in AI Agents, Generative AI, and Large Language Models (LLMs)
- Understanding of Conversational AI frameworks, Langchain etc
- Experience working with LLaMA or similar open-source LLM architectures
Key Responsibilities:
1) AI Powered Automation & Operational Scaling
- Lead the development and integration of cost effective AI systems, leveraging LLMs and AI agents to optimize business operations, automate workflows, and improve customer support processes.
- Implement AI-based self serve tools to reduce operational dependencies.
- Collaborate with product and engineering teams to integrate AI driven automation into products, customer support, and internal operations.
- Identify and implement AI tools to enhance team productivity, GTM strategies, and business scalability.
2) AI Systems Architecture & Development
- Set up evaluation frameworks for AI systems & drive experimentations to optimize performance
- Lead the development and integration of AI agents for business automation (e.g., customer support, operations, GTM workflows).
- Rapidly prototype with AI tools iterating from proof-of-concept (POC) to full-scale production deployment, aim to minimize software development costs and maximize ROI
3) Technical Leadership & Strategy
- Assist in developing AI roadmaps and strategies to drive innovation and long term efficiency.
- Ensure AI solutions align with business objectives, compliance standards, and scalability needs.
- Establish best practices for AI governance and continuously drive learning within the team.
Preferred Qualifications:
- Experience in natural language processing (NLP) and conversational AI development.
- Familiarity with cloud platforms AWS / GCP / Azure.
- Strong problem-solving and analytical skills with a focus on performance optimization.
- Excellent communication skills to collaborate with cross-functional teams effectively.
- Experience with machine learning frameworks and tools
