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.
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.
Qualifications
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.
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.
Strong spoken and written English for international collaboration