Engineering Team Lead
The role
We are looking for an Engineering Team Lead (Java) to drive product growth and technical excellence across our SaaS platform and databases. In this role, you will shape the future of our technology stack, lead a team of skilled engineers, and work closely with the CTO on key projects including core platform development and integration of AI-driven components. The ideal candidate is a senior-level Java developer with proven experience integrating ML/LLM toolkits into live SaaS environments — including hands-on implementation, resource planning, cost analysis, and infrastructure-level decision-making.
Responsibilities
Academic Qualifications
- Education: B.S., M.S., or PhD in Computer Science, Engineering, Physics, or a related technical field.
- Experience: 10+ years in Java backend development and architectural leadership roles.
- Solid understanding MLPps/LLMOps environments.
- Design, develop, and maintain scalable microservices-based systems using Java technologies.
- Make high-impact architectural and design decisions to improve performance and reliability.
- Oversee backend engineering practices including clean coding, testing, code reviews, and deployment processes.
- Collaborate closely with CEO, CTO, product managers, DevOps, and external vendors to ensure technical alignment and successful project execution.
Core Stack Expertise:
- Java (Spring Boot, Spring Framework, Hibernate)
- Microservices architecture, multithreading, concurrency, OOP, design patterns
- Messaging systems: Kafka
- Frontend integration: React (in Java-centric environments)
- Containerization and deployment: Docker, Kubernetes, GitLab CI/CD
- Cloud: AWS-based infrastructure and services for scalable SaaS platforms
- Databases: Strong hands-on experience with SQL, NoSQL (MongoDB), PostgreSQL, Apache stack, and Elasticsearch.
- Security & Optimization: Familiarity with authentication protocols (OAuth2, JWT) and performance tuning best practices.
AI/ML Integration Skills
- Assess current AI/ML models and lead efforts to integrate them efficiently into existing backend systems.
- In close collaboration with the CTO, own new AI-related initiatives, focusing on infrastructure compatibility, performance, and feasibility and costs.
- Guide the selection and integration of modern AI/ML toolkits (LLM/LM frameworks) with traditional backend architecture and large-scale MongoDB-based datasets.
- Contribute to planning and resource allocation for AI workloads in data-intensive, live production environments.
Soft Skills
- Leadership: Strong people management and project delivery capabilities.
- Mentorship: Proactive in guiding and developing engineering talent.
- Collaboration: Comfortable working in cross-functional teams including DevOps, product, and frontend.
- Language: Excellent written and spoken English.