1. Technical Leadership & Architecture Direction

• Design and develop system architecture for enterprise-grade AI Agent applications.

• Define technical strategies aligned with business goals and product requirements.

• Evaluate and implement emerging technologies (AI/ML, distributed systems, cloud-native) to enhance scalability and performance.

2. Solution Development & Implementation

• Participate in the entire software development lifecycle, from requirement analysis, design, and development to testing and deployment.

• Ensure code quality through proper coding standards, code reviews, and best practices.

• Apply modern methodologies such as TDD, CI/CD, and DevOps in microservices environments.

3. Team Management & Technical Support

• Provide technical direction, mentorship, and support to development team members in solving complex technical problems.

• Collaborate closely with cross-functional teams (Developers, BAs, QA, QC) to ensure timely project delivery and quality standards.

• Promote a culture of continuous learning, technical excellence, and knowledge sharing across the team.

4. System Quality & Reliability Assurance

• Design and implement solutions for High Availability (HA), backup, and disaster recovery.

• Optimize performance and ensure security across enterprise AI applications.

• Continuously improve system deployment, monitoring, and maintenance processes.

5. Technology Research & Innovation

• Stay current with emerging technologies and integrate them into products when appropriate.

• Guide the adoption of AI/ML technologies such as LangGraph, LangChain, and LLM models.

• Contribute to establishing best practices for AI Agent development and system scalability.