Pizza Hut Digital & Technology

Tóm tắt công việc

We are seeking a highly skilled and motivated Java Technical Leader to lead and grow a team of Software Engineers delivering scalable, secure, and high-quality backend systems. 

In this role, you will combine strong Java architecture expertise, technical leadership, and modern engineering practices, including effective use of AI-assisted tools to improve productivity, quality, and decision-making. 

You will work closely with international stakeholders, take end-to-end ownership of technical outcomes, and foster a culture of engineering excellence, continuous learning, and smart adoption of new technologies. 

Key Responsibilities: 

Technical & Team Leadership 

• Lead, mentor, and coach a team of Software Engineers, supporting their technical growth and career development. 
• Act as a hands-on technical leader, setting coding standards, architectural principles, and best practices. 
• Foster a collaborative, inclusive, and learning-oriented team culture with strong ownership and accountability. 
• Guide engineers on effective and responsible use of AI tools to enhance daily engineering work (e.g., design, coding, debugging, testing, documentation). 
• Proactively identify, troubleshoot, and resolve complex performance or scalability issues. 
• Work closely with DevOps/SRE teams to improve CI/CD pipelines, deployment reliability, and runtime stability. 
• Drive improvements in system observability, monitoring, and alerting. 
• Ensure high standards of code quality through design reviews, code reviews, automated testing, and documentation. 
• Design, develop, and review robust Java-based systems using Spring ecosystem and microservices architecture. 

Global Collaboration 

• Work effectively with cross-functional and international teams (e.g., UK, US). 
• Communicate complex technical topics clearly to both technical and non-technical stakeholders. 

AI-Augmented Engineering (Big Plus) 

• Leverage AI-assisted developer tools (e.g., for code generation, refactoring, test creation, log analysis, incident triage, and documentation) to:  
• Improve development speed without compromising quality 
• Reduce repetitive manual work 
• Support faster debugging and root-cause analysis 
• Promote best practices for AI usage, including validation of outputs, security awareness, and IP safety. 
• Explore and propose practical AI use cases in backend engineering, and system observability. 

Attractive Benefits:

• 100% salary during probation period
• Annual Leave: 18 days/ year
• Five “Recharge Days” – Extra days, in addition to company holidays.
• Flexible Friday afternoon
• Full salary insurance
• 13th-month bonus
• Gift + 1 day off for birthday
• Advanced health insurance (Generali)
• Regular engagement activities: sport clubs, internal event…
• Support Macbook and Monitor

Core Java & Backend Expertise 

• Strong expertise in Java, including OOP, multithreading, concurrency, collections, and performance tuning. 
• Hands-on experience with Spring / Spring Boot, Spring Data, Dependency Injection (DI), and transaction management. 
• Solid experience designing and building RESTful APIs and distributed microservices architectures. 
• Experience with SQL databases (e.g., PostgreSQL) and NoSQL solutions (e.g., MongoDB, DynamoDB). 
• Strong understanding of data modeling, query optimization, and backend performance tuning. 
• Hands-on experience with AWS (e.g., EKS, S3, RDS, Lambda). 
• Experience with CI/CD pipelines and modern DevOps practices. 
• Familiarity with monitoring and logging tools such as DataDog for metrics, logs, and traces. 

Ways of Working 

• Proficient with GitLab for version control and collaboration. 
• Experience working in Agile / Scrum environments. 
• Strong problem-solving skills and ability to make sound technical decisions under constraints. 
• Strong spoken and written English for international collaboration.

Bonus / Differentiators 

• Proven experience using AI tools in daily engineering work (coding, debugging, testing, design, or operations). 
• Ability to mentor others on productive and responsible AI usage. 
• Familiarity with Kubernetes (K8s): containerization, deployment, scaling, and service-to-service communication.