1. Research and Trend Analysis:
- Stay up-to-date with the latest trends and advancements in IT Technology general/generative AI.
- Identify opportunities for applying generative AI techniques to improve business processes.
2. Business Requirements Analysis:
- Collaborate with business users, SA and stakeholders to understand their needs and pain points.
- Analyze existing business processes and identify areas for optimization using generative AI.
- Consult, support end-users and suggest new optimized business processes required to fulfill business requirements.
3. Solution Proposal and Ideation:
- Give Solution to optimize IT systems.
- Design, develop the software to ensure the product delivered on time, within budgetBrainstorm.
- and propose innovative ideas for applying generative AI to address business challenges.
- Work closely with cross-functional teams to develop use cases and scenarios for generative AI applications
4. Implementation:
- Collaborate with data scientists and engineers to design and implement IT solutions/generative AI solutions.
- Translate business requirements into technical specifications for IT solutions/generative AI models.To make sure all incident which cannot be solved on previous lines of support are solved Level 3 support).
- Make the deploy package to implement into other environment (test, pilot, production) and check list to deployment.
- Updating, repairing, modifying, and developing existing development.
5. Testing and Evaluation:
- Develop test plans and conduct thorough testing of generative AI models, and business function.
- Evaluate the performance and accuracy of generative AI responses to user queries.
6. Documentation and Communication:
- Create detailed technical documentation or specification documentation for solution, including user stories, process flows, and functional specifications.
- Writing the document for the operation of the program by operators.
- Communicate effectively with both technical and non-technical stakeholders.
- Document all Business processes, reports, dashboard, business rules which capture all business requirements in the BRD documents clearly
And other tasks as line manager’s assignment.
1. Educational Qualifications
- A bachelor's or master's degree in computer science, information systems, business administration or related field, or equivalent work experience, is required
2. Relevant Experience
Must-have:
- 5 years of experience in developing backend systems and applications on the Cloud (e.g., AWS, Azure, GCP, etc.).
- Proficient in NodeJS and Python for backend system development.
- Experienced in designing, building, and contributing to system architecture at medium to large scale.
- Hands-on experience in implementing and developing systems following the Microservices model.
- Strong skills in debugging, troubleshooting, profiling, logging, and monitoring systems in production environments.
- Experience working with containerization technologies such as Docker and Kubernetes.
- Solid understanding of API design principles (RESTful; experience with GraphQL is a plus).
- Capable of optimizing performance, handling concurrency, and ensuring high availability.
- In-depth knowledge of databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, etc.).
- Strong understanding of Object-Oriented Programming (OOP) principles and/or Domain-Driven Design (DDD).
Optional:
- ~2 years of IT and business/industry work related to AI/GenAI (prefer).
- Understanding and hands-on experience in building CI/CD pipelines (Jenkins, GitLab CI/CD, GitHub Actions, etc.).
- Experience with event-driven architectures (Kafka, RabbitMQ, NATS, etc.).
- Knowledge and practical experience with cloud services such as AWS, Azure, and GCP (AWS or Azure experience is a strong plus).
- Experience in system security, including authentication, authorization, OAuth2, JWT, and Identity Server.
- Solid understanding of scalability, distributed systems, caching, and queueing systems.
